The Admissibility Protocol  ·  v1.2 in force  ·  v1.3 draft open for comment  ·  Reference runner public

Numerical
Admissibility.

An open standard for evaluating whether a consequential number produced by an AI system can actually be evidenced.

AP-1 evaluates whether a numerical result was computed rather than generated, whether the operands entering that computation trace to authoritative source data, whether execution is reproducible under a declared environment, and whether unsupported results are withheld. It is model-agnostic, architecture-neutral and industry-agnostic.

v1.2 is the version in force. v1.3 is published as a draft for public comment and is not adopted.
Comment window closes 30 September 2026. Published CC-BY 4.0 — free to use, cite, implement and apply to any system, including its author's.
The reference runner is public and MIT-licensed — executable by any party, against any system, without the author.

What is numerical admissibility?

Numerical admissibility is an evidentiary property of the production of a consequential figure by an AI system: whether the system can establish how the figure was produced, where its operands came from, whether the computation is reproducible, and whether an unsupported result would have been withheld.

AP-1 evaluates it against four evidentiary properties: whether the figure was computed by deterministic calculation from source data; whether it is traceable to a specific source value and operation; whether it is reproducible under a declared execution environment; and whether it is refusable — withheld when the data required to compute it is absent or contradictory.

A computed figure and a generated figure can be textually identical. A model may state the correct number because it performed the required computation, or because that number was probable. Inspecting the answer cannot distinguish the two, because the property in question belongs to the process, not to the text.

AP-1 therefore evaluates the evidence surrounding the production of a number rather than treating the answer as proof of its own derivation. Admissibility is assessed at the system-and-evidence level, not inferred from the numerical output itself.

AP-1 defines no pass mark.

The protocol produces a per-dimension evidence profile with declared denominators, evidence classes and limitations. The party relying on the numerical result determines what level of evidence is adequate for the particular use. A system is described, not graded.

Where AP-1 fits

Interoperability protocols establish what happened. AP-1 establishes what the number is worth.

Modern AI systems are assembled from models, agents, tools and data sources. Different protocols address different parts of that assembly. AP-1 addresses a distinct question: when such a system emits a consequential number, what evidence establishes how that number was produced?

AI · FOUNDATION MODEL · AGENT Interpretation, selection, inference A2A Agent ↔ agent communication MCP Agent ↔ tool and context TOOL · DATA · DETERMINISTIC COMPUTATION APIs, databases, calculators, engines a consequential number AP-1 The numerical evidence layer COMPUTED · TRACEABLE · REPRODUCIBLE · REFUSABLE Did the computation run, and were its operands authoritative? MISSION · BUSINESS · SAFETY SYSTEM A number acted upon, recorded, regulated or relied upon

An MCP implementation can provide evidence that a tool was called. An A2A implementation can provide evidence that agents communicated.

A protocol defines an interaction. Whether a record of that interaction is admissible evidence depends on the implementation, the logging and the trust boundary — which is why AP-1 grades invocation evidence by independence and verifiability rather than by format.

Neither establishes where the numerical values entering that computation originated, nor whether the computation was required to run at all. That is the question AP-1 measures.

MCP was contributed by Anthropic to the Linux Foundation’s Agentic AI Foundation in December 2025; A2A was contributed by Google to the Linux Foundation in June 2025 and became a hosted AAIF project in August 2026. Both are vendor-neutral, community-governed protocols. AP-1 is neither affiliated with nor endorsed by either project, the Agentic AI Foundation or the Linux Foundation.

AP-1 does not replace or compete with MCP, A2A, AI governance frameworks, security controls, model-risk frameworks or domain-specific assurance standards. It is a complementary measurement layer, and unlike an interoperability protocol it defines nothing to implement: it is applied to a system from outside.

The operand boundary

A deterministic tool can execute perfectly and still produce an unsupported result.

In one recorded case, the source data was clean, the correct deterministic tool was invoked, and it executed exactly as specified. The answer was still wrong — because the model supplied an operand that appeared nowhere in the source data.

Tool execution proves that a computation occurred. It does not, by itself, prove that the operands entering it were authoritative.

Invocation verification passed that case: the tool was called. Execution contracts passed it: the call was valid. Grounding and entailment checks passed it: a computed figure is not present in retrieved context, so entailment has no purchase. Data lineage passed it: the warehouse was clean. Output review passed it: the result was arithmetically consistent with its inputs.

The failure crosses a boundary none of those controls watch. AP-1 therefore separates computation invocation — did the required computation run — from operand provenance — did every value entering it have an evidentiary basis.

AUTHORITATIVE SOURCE DATA Clean. Lineage intact. Not the failure. GENERATIVE MODEL Selects the values it passes onward operand A appears in the source operand B appears nowhere in the source THE OPERAND BOUNDARY DETERMINISTIC COMPUTATION Invoked correctly. Executes exactly as specified. Arithmetic is exact. RELEASED FIGURE Arithmetically consistent with its inputs. Evidentially unsupported. CONTROLS THAT PASS THIS CASE Invocation verification · Execution contracts · Grounding and entailment · Data lineage · Output review Each is correct within its own scope. None watches the boundary operand B crosses.

The quantitative operand-provenance findings from the reference evaluation are withdrawn under Erratum E3 pending re-execution against the corrected ground truth. The mechanism described above is not in question; the measured rates are, and no figure for them is asserted here. See the publication record below.

The reference instrument

Public, MIT-licensed, and executable against any system without its author.

A standard is only as checkable as the instrument that applies it. The reference runner is published in full and passes on Linux, macOS and Windows across two Python versions. It reports its own suite and check totals when executed, so no count is asserted here that the instrument does not itself produce. Its conformance to the standard is executable: a machine-checkable trace from each normative clause to a test asserting the behaviour that clause requires, quoting the clause from a hash-sealed copy of the standard text. This establishes traceability from clause to test, not semantic completeness of the implementation.

REPOSITORY  github.com/zorrzai/ap1-run
LICENCE     MIT
RELEASE     ap1-runner-v1.0.0 — tagged 29 August 2026
TOTALS      Reported by run_all_tests.py at execution — assertion
            and test-function counts are shown separately
PLATFORMS   Linux · macOS · Windows, two Python versions
SCORING     Deterministic — no language model executes in the scoring path

A run against the published fixture is a demonstration, not a conformant evaluation.

A question set is burned the moment it is run, and publishing it confirms the burn. The fixture shipped with the runner is published, and is therefore burned. It exists so that the instrument can be exercised and inspected — not so that a result can be claimed. No figure produced from it is an AP-1 result, whoever runs it, including its author.

A conformant evaluation requires a freshly constructed set built to the published method, with the per-dimension minima met and the independence requirements satisfied.

The burn rule governs conformance evidence, not instrument development. Published fixtures remain useful for testing, regression, demonstration and independent inspection; they cannot support a held-out conformance claim.

Run it against anything

Including systems the author did not build, and including the author's own. No involvement, cooperation or consent is required, and none can be withheld.

Executable conformance

A machine-checkable trace from each normative clause to an executable test asserting the behaviour that clause requires, quoting the clause from a hash-sealed copy of the text. Traceability is established mechanically rather than asserted; it is not a claim of semantic completeness.

Planted-defect suite

A set of deliberately introduced defects used to characterise what the instrument does and does not catch, so its own detection behaviour is measured rather than assumed.

Evaluation dimensions

Seven dimensions, reported separately.

A conformant evaluation reports every dimension with its sample size and evidence class. There is no aggregate score, so a strong result on one dimension cannot conceal a failure on another.

D1  Accuracy

Whether the figure is correct against ground truth reproducible from the published fixture.

D2  Determinism

Whether an identical question returns an identical answer across repeated runs — and by what mechanism: structurally, by configuration, or merely observed.

D3  Provenance

Whether the system can produce the source and the operation for every figure it states.

D4  Refusal integrity

Whether the system declines when the data cannot support an answer, rather than producing one.

D5  Adversarial resistance

Whether the system holds under sustained pressure to state a figure that does not exist.

D6  Conflicting input

Whether contradictory, stale, partial or out-of-range source data is detected rather than computed over silently.

D7  Computation invocation

Whether the required deterministic computation actually executed — and whether invocation is guaranteed rather than merely observed.

D7.1 invocationD7.1b instruction removedD7.2 computation correctnessD7.3 transcriptionD7.4 invocation under pressure

V1.3 DRAFT — NOT ADOPTED
The draft splits D7.2 into operand provenance D7.2(a) and operation correctness D7.2(b), and grades invocation evidence EV-0 to EV-3 by independence and verifiability.

The distinction

A system that invokes computation correctly on sampled questions has demonstrated a tendency. A system in which invocation cannot be declined has established a control. AP-1 measures which one is present.

Where numerical admissibility applies

Different regulators, different vocabularies, one requirement: show that the number was derived, not asserted.

AP-1 is architecture-neutral, model-agnostic and domain-neutral. It applies wherever a statistical component participates in producing a number that is acted upon, and an existing regime already requires that figure to be evidenced, traceable, validated or reproducible.

Financial services

SR 26-2, OCC Bulletin 2026-13 and FDIC FIL-15-2026 (17 April 2026) superseded SR 11-7. Footnote 3 places generative and agentic AI outside the scope of that guidance while confirming the principles still apply to traditional statistical models and to non-generative, non-agentic AI. The practical consequence, as noted by counsel and model-risk advisers, is that each institution defines, documents and defends its own governance for these systems. UK expectations include independent validation within SS1/23. The EU AI Act requires record-keeping and consistent accuracy, robustness and cybersecurity for high-risk systems.

SR 26-2 fn.3OCC 2026-13FDIC FIL-15-2026PRA SS1/23EU AI Act Art. 12, 13, 15, 19

Pharmaceuticals, biotech & clinical

Electronic records and regulated data are subject to requirements for validation, secure audit trails, traceability and protection against unauthorised alteration. FDA data-integrity practice commonly expresses these principles through ALCOA+, alongside 21 CFR Part 11 and related requirements.

21 CFR Part 11ALCOA+EU Annex 11ICH E6(R3)

Aerospace & aviation

Software assurance requires traceability from requirement to implementation to verification evidence. Where a statistical component supplies a value to a qualified computation, the provenance of that value falls outside the tool qualification of the computation itself.

DO-178CARP4754ADO-330

Space & mission systems

Model and simulation credibility assessment, software classification and verification evidence regimes all require that computed values be defensible rather than asserted.

M&S credibilityV&VSoftware assurance

Defense

The US defense industrial base comprises a large population of private companies operating under assurance and cybersecurity obligations. Decision-support and autonomous systems producing consequential figures raise the same evidentiary question.

CMMC 2.0DFARS 252.204-7021

Nuclear

Safety-analysis codes operate under software quality assurance regimes requiring verification, validation and configuration control. A value entering a safety calculation from a statistical component sits outside the qualification envelope of the code.

10 CFR 50 App. BASME NQA-1

Insurance & reinsurance

Quantitative requirements govern the valuation of assets and liabilities and the calculation of capital, alongside own risk and solvency assessment and supervisory reporting. A reserving or pricing figure that cannot be traced to its inputs cannot be validated.

Solvency IIORSANAIC

Electric power & utilities

NERC-registered entities operate under mandatory reliability standards carrying evidence and audit obligations. Figures informing dispatch, capacity and protection decisions carry the same requirement.

NERC Reliability StandardsCIP

Medical devices & diagnostics

Software as a medical device operates under lifecycle, risk-management and validation regimes. A computed clinical value must be verifiable rather than asserted.

IEC 62304ISO 13485EU MDR

Rail & maritime

Safety-related signalling and control software carries software integrity level obligations with verification evidence; classification regimes apply comparable requirements at sea.

EN 50128 / 50716IMO

Audit & financial reporting

Internal control over financial reporting requires that figures entering statements be supported by evidence a third party can examine and reproduce.

SOX 404PCAOB

Any domain that computes

The mechanism is not sector-specific. It appears wherever a statistical component supplies operands to a deterministic calculation whose output is acted upon — including sectors not listed here.

Domain-neutral by design

AP-1 measures whether a system produces evidence relevant to these obligations. It does not confer compliance with any of them, and is not a substitute for the applicable regulatory, engineering or quality process. Regulatory descriptions above are indicative summaries and are not a statement of scope or application. The financial-services mapping is set out with its primary sources in Appendix A of AP-1 v1.2, whose instruments and article numbers were verified against primary sources as of July 2026. Mappings for the other sectors listed here are indicative only and are not carried in the standard.

Publication record

Every version dated, deposited and permanently citable.

The standard is versioned at document level. Prior versions remain permanently citable; no version is withdrawn or silently altered. A claim of compliance must cite the specific version evaluated against.

VersionDateStatusRecord
v1.0Jul 2026Initial publicationSuperseded — permanently citable
v1.1Jul 2026D7 prior-work citation; capability vs controlSuperseded — permanently citable
v1.215 Jul 2026In forceDeposited · 10.5281/zenodo.21369899
Pre-registration2026Measurement methodology and analysis plan, frozen before executionOSF · timestamped, immutable
Erratum V126 Jul 2026Eight defect classes recorded; affected findings withdrawnPublished in full
v1.330 Jul 2026Draft for public comment — not adoptedComment window closes 30 Sep 2026 · 10.5281/zenodo.21755443
Reference runner29 Aug 2026Tagged release ap1-runner-v1.0.0, published under MIT licence. Suite and check totals are reported by the runner at execution.github.com/zorrzai/ap1-run
IDENTIFIER      AP-1 — The Admissibility Protocol
CONCEPT DOI     10.5281/zenodo.21324954  (resolves to latest deposit)
V1.2 DEPOSIT    10.5281/zenodo.21369899  (in force — cite this)
V1.3 DEPOSIT    10.5281/zenodo.21755443  (draft for comment, not adopted)
PRE-REGISTRATION osf.io/y97d8  (methodology frozen before execution)
IN FORCE        v1.2
DRAFT           v1.3 — public comment, not adopted
WINDOW          Closes 30 September 2026
LICENCE         Creative Commons Attribution 4.0 (CC-BY 4.0)
AUTHOR          Marcus Rupp
PUBLISHER       ZORRZ Financial Inc.
REPOSITORY      github.com/zorrzai/admissibility-protocol
INSTRUMENT      github.com/zorrzai/ap1-run  (MIT)

What is published

The standard is reproducible without its author. The following are public and independently checkable:

Standard — v1.2 and v1.3 draft

Full text in Markdown and PDF, deposited with a persistent DOI.

Reference evaluation

Complete results reports for the two published runs, with their sealed configurations and per-dimension profiles. Affected findings are withdrawn under the errata above.

Correction record

Five recorded defects across two series, in the author's own standard and instrument. Affected findings are withdrawn rather than restated, and the frozen run artifacts are left unmodified.

Frozen run artifact

The raw evaluation log as executed, sealed and unmodified.

Pre-registration

Hashes, commit identifiers, model identifiers and timestamps recorded before execution.

Evaluation harness

The runner and classifier used to produce the reference evaluation, published in full under MIT licence. Runnable in one command against any system, and it reports its own totals.

Pre-registered methodology

The measurement methodology and analysis plan, deposited on the Open Science Framework and frozen before execution — timestamped and immutable.

Sealed evaluation set

The question set and answer key, published on execution and therefore burned.

Disposition record

Comments received on the v1.3 draft and their disposition, recorded whether accepted or not.

Citation metadata

Machine-readable citation file, contribution rules and security policy, so the standard can be cited and challenged without contacting its author.

Amendment template

The issue template through which any party may propose a change to the standard, and the channel through which the comment window is run.

Version history

Every prior version remains retrievable and permanently citable. No version is withdrawn or silently altered.

How to cite

Rupp, M. (2026). The Admissibility Protocol (AP-1): An Open Standard for
Evaluating Numerical Admissibility in AI Systems, Version 1.2.
ZORRZ Financial Inc.
Version DOI: 10.5281/zenodo.21369899   (v1.2 — the exact text)
Concept DOI: 10.5281/zenodo.21324954   (resolves to latest deposit)

@misc{ap1_2026,
  author       = {Rupp, Marcus},
  title        = {{The Admissibility Protocol (AP-1): An Open Standard for
                  Evaluating Numerical Admissibility in AI Systems}},
  year         = {2026},
  version      = {1.2},
  publisher    = {ZORRZ Financial Inc.},
  doi          = {10.5281/zenodo.21369899},
  note         = {Concept DOI 10.5281/zenodo.21324954 resolves to the latest deposit},
  url          = {https://numericaladmissibility.org/}
}

Cite the version, not the concept.

Per §0.4.2, the concept DOI cites the standard generally and always resolves to the latest deposit. A version DOI cites the exact text an evaluation was frozen against, and shall be used in any evaluation report alongside the version number.

This matters right now. The concept DOI currently resolves to the v1.3 draft deposit, which is published for comment and not adopted. A reader following the concept DOI expecting v1.2 — the version in force — will land on the draft. Any evaluation claiming conformance to v1.2 must carry the v1.2 version DOI explicitly.

AP-1 v1.3 draft deposit: 10.5281/zenodo.21755443. Not adopted; not a conformance target.

Correction record

Every defect found in this standard and its instrument, published in full, including the ones that cost the headline figures.

Two independent series are maintained, in two repositories, against two different objects. They are not a single sequence and should not be cited as one.

IDDateDefectEffect on published figures
Series 1 — reference evaluation  ·  admissibility-protocol / ERRATUM_V1.md
V126 Jul 2026Eight defect classes recorded in the V1 reference evaluationAffected findings withdrawn
Series 2 — published findings  ·  ap1-run / FINDINGS_ERRATA.md
E112 Aug 2026F6 per-item summary attributed originated operands to the wrong mechanisms and placed global totals inside per-item parentheses. The population table above it was correct throughout; the error was in the prose.None. Prose corrected by generating per-item breakdowns dynamically from the artifact.
E228 Aug 2026F3 stated that the platform rejected temperature=0 and that this was observed under both models. Temperature was never transmitted in either run — it was a structured omission the adapter drops from the request body — so the platform was never given the opportunity to reject it. Sampling was also partially pinned rather than absent.None. The OBSERVED-ONLY classification stands; the stated basis for it was wrong.
E328 Aug 2026The Q07 derivation declared a constant that its computation never used. The resolution ladder treats a declared constant as grounding, so that operand resolved as grounded rather than originated, and downstream invocations inherited the grounding through transitivity.D7.2(a) operand-provenance counts and percentages withdrawn for both runs. Not to be cited.
E429 Aug 2026The run disclaimer embedded in four published artifacts per run stated that R2.4 was not built. R2.4 is built, is reported in the findings, and is validated by a phase exit gate. Two published artifacts from the same run contradicted each other.None. The disclaimer understated the instrument. Run artifacts left unedited; source corrected for future runs.

Why E3 was withdrawn rather than corrected.

The obvious remedy is to re-score the stored transcripts against the corrected constant set. That remedy is not available. The provenance classifier changed across three commits since the runs, one of them during the second run's execution, so re-scoring would apply the constant correction and every classifier change since, and could not separate them. The classifier's tool-call grouping also changed, which alters the invocation population itself rather than only the per-invocation outcome. Two re-scoring attempts produced materially different results, and one produced a grounded-plus-originated total exceeding the invocation population.

AP-1 §5.8 requires re-execution rather than re-scoring across a ground-truth revision. That clause was applied to the publisher's own evaluation, at the cost of withdrawing the most prominent quantitative findings from the published record.

How E3 was found, which is the part that matters.

It was found by verify_run_seal.py on its first execution, checking whether a published run's seal reproduced from its published artifacts. It reported a ground-truth hash mismatch on both runs, which led to the diff and then to the unused constant. Twelve adversarial review passes over the same repository did not find it. The constant had been removed eight days earlier as a documentation cleanup, with no mechanism indicating that the edit invalidated two sealed runs.

This is the argument for mechanical verification stated against the publisher's own work: a seal that is checked catches what careful reading does not. It is also the reason the seal verifier exits non-zero on these runs and will continue to, rather than being reset to green.

No operand-provenance rate is asserted anywhere on this site or in the current findings. The mechanism the reference evaluation was built to demonstrate is not in question; its measured magnitude is, and it will be re-established only by re-execution against a tagged release.

Prior art and adjacent work

AP-1 does not originate the ideas it rests on.

The policy-versus-control distinction, the deterministic-layer remedy for numerical fabrication, and admissibility as a property of a system rather than of an output all appear in prior and concurrent work. AP-1's contribution is a versioned, openly licensed measurement protocol that operationalises these distinctions at the level of an individual consequential numerical output, with declared evidence classes, declared denominators, held-out evaluation requirements and a stated defeat condition. This record is indicative, not exhaustive; the field is active and further work is expected.

AreaWorkRelationship to AP-1
Tool-execution contractsContract-grounded and verified tool execution; pre- and post-conditions on tool callsEnforcement mechanism. A contract governs the call, not the provenance of the values crossing into it.
Argument-level provenanceProvenance-aware tool arguments and capability-based information-flow control for agentsEnforcement at the boundary AP-1 measures. Complementary: these prevent, AP-1 establishes whether prevention is present and guaranteed.
Execution provenanceAgent execution traces and evidence tracing as an emerging research areaSame concern, broader unit. AP-1 narrows to the numerical operand and the deterministic computation.
Tool invocation as capabilityBenchmarks measuring whether a model judges correctly when a tool is requiredMeasures the model's decision quality. AP-1 asks whether the decision is the model's to make at all.
Deterministic inferenceBatch-invariant kernels eliminating run-to-run nondeterminismEngineering counterpart to D2, one layer down: removes a source of nondeterminism rather than measuring what remains.
Governance frameworksAI management systems, risk frameworks and sector assurance standardsAddress organisational and lifecycle processes. AP-1 measures one narrow technical property inside such a programme.

The distinction that defines the layer.

The adjacent work above is largely enforcement: mechanisms that prevent an unsupported value from crossing into a computation. AP-1 is measurement: the instrument that establishes, for a deployed system, whether such a control exists, whether it is guaranteed rather than observed, and what evidence supports the figure that emerged.

Governance and independence

A standard authored by an interested party is credible only if it is reproducible without the author, falsifiable against the author's own product, and governed in the open.

StatusPosition
OriginFounder-published open standard. Authored by Marcus Rupp; published by ZORRZ Financial Inc.
LicenceCC-BY 4.0 — permanent, irrevocable
CostNone. No fee of any kind.
RegistryNone
CertificationNone. AP-1 does not certify, license, accredit or endorse any system.
Reference instrumentPublished under MIT licence — executable by any party, against any system, without the author
Independent stewardNot yet established
Public amendment processYes — open comment window with published disposition record
Reference evaluationAuthor-run case study; defects published, affected results withdrawn
Independent evaluationNone completed to date

Path to independent stewardship

Independence is a stage, not a claim. The intended progression is published so that the current position is unambiguous.

1  Founder-originated

ZORRZ authors and publishes the standard, its reference evaluation and its defects. Current position.

2  Open technical review

Independent reviewers reproduce the harness and challenge the standard through the public amendment process. Now possible without the author: the instrument is public.

3  Independent application

Third parties execute AP-1 against systems the author did not build, and publish results — favourable or otherwise.

4  Independent stewardship

Custody of the standard transfers to a body with no commercial interest in any evaluated system.

5  Multi-party governance

A technical steering group and published maintainer process govern amendment.

Where this stands

Stages 2 and 3 are open. Independent reviewers and independent applications are invited; the standard and its instrument are designed to be run without the author's involvement or consent.

Disclosure. AP-1 is authored by Marcus Rupp and published by ZORRZ Financial Inc. ZORRZ does not build systems evaluated under the standard. The author holds a commercial interest, through a separate company, in systems designed to satisfy it. This is a conflict of interest and is disclosed as one.

No independent steward currently holds the standard or its reference implementation. No independent application of the standard has yet occurred. The reference evaluation is an author-run case study whose defects are published in full as errata, and whose affected results are withdrawn. Its fixtures and expected values were authored with the assistance of an AI coding agent rather than derived by an independent party; no language model executes during an evaluation run.

Where independent implementation, independent scoring, independent review or domain-expert validation is required by the standard, those requirements are identified as unmet rather than represented as satisfied.

The purpose of this disclosure is not to claim independence. It is to make the provenance of the standard and its evidence visible, so that any party may challenge, reproduce, rescore or reject its conclusions.

A stated defeat condition

AP-1 rests on a claim that can be proven false, and publishes the condition under which it would be. As stated in §2.5 of the version in force: a system relying on probabilistic generation to decide whether to compute, to decide which values enter the computation, or to transcribe the result, cannot guarantee admissibility.

It is falsified by a single counterexample. Any system that admits a generative model into the decision to compute and nonetheless achieves, on a held-out set it has not seen, 100% invocation of deterministic computation on computable questions including with any facilitating instruction removed, exact reproducibility across repeated execution, and zero origination across the refusal-pressure and adversarial conditions, has refuted the claim — and AP-1 records that refutation unaltered.

Stated in the instrument's own terms rather than as an absolute: a finite sample with no failures does not establish that the failure rate is zero. Such a result is reported with its denominator and its one-sided upper bound on the failure rate, as the runner requires of every other result, including the publisher's.

A standard that cannot be falsified is not a standard. Any party is invited to attempt it, expressly including the builders of frontier generative models.

The defeat condition is itself under challenge — filed by the publisher.

The condition above is v1.2’s, the version in force. The v1.3 draft reformulates it, and comment C-12 — filed by the publisher against its own draft — argues that the reformulation cannot be satisfied. The draft’s §2.5(a) requires invocation guaranteed rather than observed, achieved by generative means alone and without any deterministic containment mechanism. But D7.5 holds that no observed rate, including 100% at any n, establishes a guarantee, and that only the structural evidence of §6.3(b) converts an estimate into a control claim — and §6.3(b) requires a named architectural mechanism making origination unrepresentable, which is deterministic containment, the thing §2.5(a) excludes.

Condition (e) compounds it. “Zero origination” is asked of a finite sample: at D5’s minimum of twenty items, a sample with no failures yields a one-sided 95% upper bound near 14%. The refutation route is closed by the standard’s own machinery, and on that reading the invitation to refute is generous in tone and empty in logic.

The proposed resolution for v1.4 is to restate (a) as a threshold achievable in principle — invocation established at EV-2 or better across a stated n, with the bound reported — or to withdraw the falsifiability claim. The second is preferable to a claim that cannot be met. Until v1.4 is adopted, this section describes an aspiration whose current formulation the publisher has argued against in the open comment record.

Methodology

A measurement protocol, not a benchmark or a certification programme.

Deterministic scoring

No language model executes in the scoring path. Classification, numeric comparison and provenance resolution are deterministic and re-runnable.

Pre-registration

Fixtures, questions and expected values are hashed and sealed before execution, so the evaluated material can be independently reproduced.

Evidence classes

Results carry the evidence class under which each observation was established. A self-reported signal is not treated as equivalent to an externally verified one.

Burned question sets

A set is burned the moment it is run, and publishing it confirms this. Every evaluation uses a freshly constructed set; the method is published, not a reusable set.

Declared limitations

Known limitations, unmet independence requirements and methodological defects are reported rather than omitted.

Observation versus structure

An observed rate is not treated as a universal guarantee. A structural mechanism that makes a failure unrepresentable is stronger evidence than an absence of failure in a finite sample.

Ground truth is a separate question

Deterministic scoring does not imply independent ground truth. The expected values in the published fixture were authored with AI coding assistance, not derived by an independent party. Independent construction of expected values is therefore treated as a separate conformance requirement, and is currently unmet.

Declared authority, measured conformance

AP-1 does not designate which sources are authoritative, nor does it establish whether a source is correct. The source hierarchy, permitted transformations and declared constants must be fixed before execution; AP-1 measures conformance to that declared evidence chain.

Re-execution, not re-scoring

Results are not portable across a revision of the ground truth. Where the fixture or its expected values change after a seal, the correct remedy is re-execution — as applied to the author's own withdrawn findings.

Common questions

Why can output inspection not establish whether an AI figure was computed?

A computed figure and a generated figure can be textually identical. A model may state the correct value because it performed the computation, or because that value was probable. The property being evaluated belongs to the process that produced the figure, not to the answer text.

Why is tool-call logging insufficient?

Tool-call logging records that a tool was invoked and with what arguments. It does not record where those arguments originated. A correctly functioning deterministic tool can therefore return a mathematically correct result computed over an unsupported operand.

What is operand provenance?

The evidentiary relationship between a numerical operand entering a computation and the authoritative source data from which it is claimed to derive — either appearing verbatim, or derived by a declared deterministic transformation recorded at the point of derivation.

Is the reference instrument public?

Yes. The runner is published at github.com/zorrzai/ap1-run under the MIT licence and runs in one command, reporting its own suite and check totals at execution. Its conformance to the standard is itself executable, with one test per clause quoting the clause from a hash-sealed copy of the text. Note that a run against the fixture shipped with it is a demonstration rather than a conformant evaluation, because a published question set is burned.

Who decides which sources are authoritative?

Not AP-1. The relying system, the domain authority or the evaluation fixture must declare the source hierarchy, the permitted transformations and any declared constants before execution. AP-1 measures whether the released figure conforms to that declared evidence chain. It does not adjudicate whether a designated source is itself correct, current or complete, and it is not a theory of what makes data authoritative. Where two sources conflict, are stale, are partial or fall out of range, that is measured under D6 as a property of the system's handling, not resolved by the protocol.

This boundary is deliberate. A measurement standard that also decided what counts as truth would be unfalsifiable, and could not be applied to domains its author does not understand.

How does AP-1 relate to MCP and A2A?

MCP addresses agent-to-tool interaction; A2A addresses agent-to-agent communication. Both concern interoperability. AP-1 concerns the evidentiary integrity of the consequential numerical result emerging from such a system. It neither competes with nor replaces either protocol.

How does AP-1 relate to AI governance frameworks?

Governance frameworks address organisational, management, risk and lifecycle processes. AP-1 measures one narrow technical property inside such a programme: whether the deterministic computation required to produce a figure executed, and whether its operands were admissible. It is complementary and substitutes for none.

Is AP-1 specific to financial services?

No. AP-1 is architecture-neutral, model-agnostic and domain-neutral. Its empirical evidence base to date is drawn from language-model systems, and that scope limitation is stated in the standard. Application to other model classes and domains requires appropriate domain-specific evaluation.

Does AP-1 certify systems or award a mark?

No. AP-1 issues no certification, maintains no registry and charges no fee. It produces a per-dimension evidence profile and sets no pass threshold. A system is described, not graded.

Can I run AP-1 without the author's involvement?

Yes, and that is the design intent. The standard, the scoring rules, the disclosure checklist, the held-out-set construction methodology and the evaluation harness are published. The runner is at github.com/zorrzai/ap1-run under MIT licence and runs in one command. Any party may apply AP-1 to any system — including ZORRZ's — without the author's involvement, cooperation or consent. The author cannot suppress, gate or condition an evaluation.

May I fork, adapt or republish AP-1?

Yes. The licence is CC-BY 4.0 and permits it, subject to attribution. Independent application by parties with no commercial relationship to the author is regarded as the primary evidence of the standard's validity — including evaluations reporting results unfavourable to the author, which will be linked from the repository.

How to comment on v1.3

The window closes 30 September 2026. Every substantive comment receives a published disposition.

AP-1 v1.3 is a draft. It is not adopted, and it will not be adopted without a public comment period. Comments received in this window shape what becomes v1.4. The standard is not revised silently, retroactively, or to accommodate any single system's result.

Route 1  ·  Repository issue

Open an issue using the amendment template. Threaded, permanently archived, and citable by issue number in the disposition record. Preferred where you are comfortable with the platform.

Open an amendment issue →

Route 2  ·  Email

Send to the address below with AP-1 v1.3 comment in the subject. Emailed comments are transcribed into the public record under the sender's name, so both routes produce one archive rather than two.

dev@zorrz.com →

What happens to your comment

Every substantive comment is recorded in the public disposition record with its resolution — accepted, accepted in modified form, declined with reasons, or deferred to a successor protocol. Declined comments are published alongside accepted ones.

Disposition record →

Comment rules

ItemPosition
WindowOpens on publication of the v1.3 draft; closes 30 September 2026. Late comments are recorded and carried to the following revision rather than discarded.
AttributionComments are public and attributed to the sender by name and, where given, affiliation. Anonymity is available on request and does not reduce the weight given to a comment.
AffiliationStating an employer is optional. A comment made in a personal capacity is recorded as such and implies no institutional position or endorsement.
ScopeAny part of the draft, including the framing, the versioning decision, and whether a proposed change belongs in a successor protocol rather than a point release.
DispositionEvery substantive comment receives a recorded resolution. Comments are not resolved privately.
ConflictsA comment from a party with a commercial interest in an evaluated system is recorded with that interest disclosed. This applies to the author's own comments.

What makes a comment actionable

A comment that identifies a specific clause and states what is wrong with it produces a change. A general objection cannot be dispositioned, however well founded.

Cite the clause

Reference the section or dimension. A comment on “the provenance requirement” is harder to act on than one on a numbered clause.

State the defect, not the preference

Whether a requirement is unmeasurable, ambiguous between two readings, circular, or produces a false result in a stated case.

Give the failing case

A system, configuration or scenario in which the clause as written yields the wrong verdict is the most useful contribution possible.

Propose replacement text

Optional, and welcome. Text that can be adopted directly is faster to disposition than a description of the problem alone.

Say if it is out of scope

If a proposed change alters the dimension set or the conformance bar, it may belong in a successor protocol. Views on that boundary are explicitly invited.

Disagreement is the point

The standard names its own defeat condition. A comment arguing that AP-1 measures the wrong property, or measures it wrongly, is more valuable than one confirming it.

Open questions the author is unsure about. The draft carries fourteen questions on which the author holds no settled view — including whether the operand-provenance sub-dimension belongs in a point release or a successor protocol, whether the structural-evidence requirement changes the conformance bar, and how the reverse traversal should behave where a declared transformation is lossy.

These are listed in the draft. A reader who answers one of them has contributed more than a reader who endorses the whole.

The question

Not merely: did the AI produce the number?

But: what evidence establishes how the number was produced, where its operands came from, whether the computation is reproducible, and whether the result should have been released at all?

That question becomes consequential as statistical models participate directly in systems whose numerical outputs are acted upon, recorded, regulated or relied upon as engineering evidence. AP-1 defines a common vocabulary and a measurement procedure for it.