Human Revision and Decision Record
What changed, who recorded the decision, why, and which provenance or review records are missing?
Worked example
A briefing team can preserve an original statement, its proposed correction and the recorded reviewer decision. Keep unresolved changes visible through handoff.
Preserves the original suggestion, subsequent human decisions, supplied input references, and visible audit gaps.
Try it yourself
The calculator opens with the fictional example already filled in. Change one input, choose Calculate locally, and compare the result to the original values below. Use Reset fictional fixture to start over.
An unknown result means the available inputs do not support a value. Check the calculator’s Warnings tab for what is missing or uncertain.
- Supplied human decision records 1 records
- Decisions differing from known predecessor 1 records
- Visible audit gaps 0 gaps
Import local JSON or CSV
Files stay in this browser. Maximum 1 MiB. JSON imports are recalculated. CSV supports flat observation tables, with column types taken from the displayed fixture. Empty cells become null.
Compare the arrangements
Keep physical resources and evaluation conditions equal. With identical inputs, all three approaches produce identical arithmetic. The comparison refuses material differences in declared conditions; it does not verify those declarations.
Privacy: comparison inputs may contain sensitive notes or operational details. Storage is off by default. Do not enter personal records or sensitive infrastructure details. Reproduction exports include supplied inputs and notes, including raw small-cell inputs suppressed from CORE-009 result tables. Suppression of displayed results does not make a reproduction export safe to publish.
Executive brief and reproducible export
Review for personal, confidential or sensitive material before saving or sharing. No automatic submission occurs.
Read the generated brief
Method, inputs and limits
Preserves the original suggestion, subsequent human decisions, supplied input references, and visible audit gaps. Method version 0.2.0. Cannot prove authenticity, make records tamperproof, establish legal evidence, or validate the merits of a human decision.
| Input | Unit / type | Required interpretation |
|---|---|---|
| original — Original suggestion and input references | record / json | ID, suggestion, methodVersion, explicit timestamp, inputReferences with ID, version and checksum. Optional checksumAlgorithm of sha256 requires 64 hexadecimal characters. |
| revisions — Append-only human decision records | records / json | Each record preserves previousId, decision, reviewer name/placeholder and role, timestamp, reason, and evidenceReferences. |
Visible mathematics / decision rules
changed(i) = decision(i) differs from the previous supplied decision/suggestion.
Audit gaps = missing evidence/checksum/version, unknown or non-latest predecessor, or non-monotonic supplied timestamps.
The latest reviewed decision requires a continuous, chronological chain of reviewed records. Pending, branched or missing links leave the latest decision unresolved.
What this result cannot establish
- The record is an ordered input ledger with exact text replacement diffs, claim/source metadata, review status, and supplied correction-acknowledgment times; it is not a secure log service.
- The original suggestion and all subsequent decisions remain in the output. Labels and references are user-supplied; identity and evidence authenticity are not verified.
- Checksums and canonical text enable external comparison but do not prevent replacement, tampering, or a false source record. The export layer may compute SHA-256 separately.
- Timestamps are supplied explicitly. No current clock, network lookup, legal-evidence claim, or automatic approval is used.
What would falsify the assumptions?
- An independently preserved source, contradictory timestamp, missing amendment, or unrecognized reviewer can contradict this ledger.
- Ask the designated reviewer to confirm the original record, revision chain, evidence, and stated reasons.
- This is record preservation, not resource creation or a causal estimate. A manual append-only log can produce the same result.
- MAR adds no demonstrated benefit when manual logging preserves the same trail; overwritten suggestions or false provenance would add risk.
- Assumptions fail if the supplied definitions, units, period, scope or source records are wrong or incomplete.
- An independent source audit or replication may contradict an input or the recorded dependency.
- This method creates no resources. Physical conservation is checked in the inventory and transfer ledgers; descriptive graphs and checklists are not resource-flow models.
- The same equations and review checklist can be reproduced with a spreadsheet or structured human-only process.
- This is deterministic arithmetic, a descriptive comparison or a structured governance check, not a fitted causal effect or forecast. Fictional inputs remain an exercise.
- Equal or worse measured errors, net review effort, disclosure burden or fallback under MAR would show no added benefit or added risk; no improvement is assumed.
Reproducible fictional fixture and independently calculated expectations
This fixture is synthetic. It does not describe a country, government, company or event.
{
"observations": {
"unit": "records",
"origin": "synthetic",
"sources": [
{
"id": "SYN-001",
"kind": "synthetic",
"label": "Fictional example",
"url": null
}
],
"original": {
"id": "SUG-1",
"claimId": "CLAIM-1",
"originalDocument": {
"id": "DOC-1",
"sourceAuthor": "Fictional service office",
"availability": "public",
"reference": "SYN-001 fictional public document"
},
"suggestion": "Allocate 10 fictional staff-hours to service A.",
"methodVersion": "0.1.0",
"timestamp": "2027-01-01T09:00:00Z",
"inputReferences": [
{
"id": "SYN-001",
"version": "fixture-1",
"checksum": "synthetic-reference-not-a-verified-digest"
}
]
},
"revisions": [
{
"id": "DEC-1",
"previousId": "SUG-1",
"decision": "Allocate 8 fictional staff-hours to service A.",
"reviewStatus": "human-reviewed",
"publicAvailability": "public",
"acknowledgedAt": "2027-01-01T12:00:00Z",
"reviewer": {
"nameOrPlaceholder": "Reviewer A (fictional)",
"role": "Civilian service coordinator"
},
"timestamp": "2027-01-01T10:00:00Z",
"reason": "Preserve 2 staff-hours for the explicitly declared local minimum.",
"evidenceReferences": [
{
"id": "SYN-001",
"version": "fixture-1",
"checksum": "synthetic-reference-not-a-verified-digest"
}
]
}
]
},
"parameters": {}
}Expected checks
{
"revisionCount": 1,
"changedDecisions": 1,
"auditGaps": 0
}Download input fixtureAuthoritative background references
- NIST: AI Risk Management Framework — Voluntary governance background; not validation of MAR. Reviewed 2026-11-09. Reference, not endorsement or validation.
These sources inform definitions or review practices. They do not validate this implementation or endorse MAR.