Anonymous Source Justification Editorial Checklist

Caller independently verified knowledge, corroboration, motive, necessity and editor authorization criteria for anonymous source review; anonymity alone not credibility. Independently declared positive evidence requirements; overlaps and unknowns retained. Caller independently verifies context, evidence, reference edition and applicability; not factual authenticity, current legal advice or publication clearance.

Description

Anonymous-source review concerns verification, attribution agreements and editorial justification.

Anonymous-source review concerns verification, attribution agreements and editorial justification.^[1]

Organizing declared evidence does not authenticate the source or guarantee anonymity. The tool compares your observed and known flags with your declared positive requirements, retaining unresolved candidates.

When to use Anonymous Source Justification Editorial Checklist

Use this tool to calculate or review the supplied observations under the stated rules. Establish the reviewed evidence, house style or applicable jurisdiction and dated reference.

How to use Anonymous Source Justification Editorial Checklist and understand its results

Establish the reviewed evidence, house style or applicable jurisdiction and dated reference.
Enter callerAnonymousSourceClassIds, callerAnonymousSourceRequirements, observedAnonymousSourceEvidence, knownAnonymousSourceFlags, using the field meanings and rules below, then run the tool.
Read compatibleCallerClasses, fullyWitnessedCallerClasses, using the output meanings and calculation rules below. Distinguish compatible candidates from fully witnessed classes; compatibility can retain unknown required evidence.
Correct any reported input issue and run again. Before using a successful result, check the stated units, signs, reference scope and observation coverage.

Input field	Meaning	Value type	Requirement
callerAnonymousSourceClassIds	Caller anonymous source class ids	list of string	Required
callerAnonymousSourceRequirements	Caller anonymous source requirements	numeric matrix	Required
observedAnonymousSourceEvidence	Observed anonymous source evidence	list of number	Required
knownAnonymousSourceFlags	Known anonymous source flags; binary 1 means the matched observation is known, 0 means unknown	list of number	Required

Use unique nonblank class IDs and a nonempty binary requirement matrix aligned by class and evidence column. Every class must require at least one positive feature. A one requires presence; zero ignores the feature and does not require absence. Supply binary observed evidence and known flags. A known required zero excludes a class; an unknown required feature retains compatibility but prevents full witnessing. Return all compatible classes and the subset with every required feature known and present. Classes may overlap.

compatible_c=∀j(requirement_cj=0 or known_j=0 or evidence_j=1); witnessed_c=∀j(requirement_cj=0 or (known_j=1 and evidence_j=1))

Use the matching field units and the exact boundary, ordering and reference rules above.

Output field	Meaning	Value type
compatibleCallerClasses	Compatible caller classes	list of string
fullyWitnessedCallerClasses	Fully witnessed caller classes	list of string

json

{
  "input": {
    "callerAnonymousSourceClassIds": [
      "a",
      "b"
    ],
    "callerAnonymousSourceRequirements": [
      [
        1,
        0
      ],
      [
        0,
        1
      ]
    ],
    "observedAnonymousSourceEvidence": [
      1,
      0
    ],
    "knownAnonymousSourceFlags": [
      1,
      0
    ]
  },
  "output": {
    "compatibleCallerClasses": [
      "a",
      "b"
    ],
    "fullyWitnessedCallerClasses": [
      "a"
    ]
  }
}

Limitations and assumptions

Annotations and applicable policies must be independently reviewed. The tool does not authenticate facts, establish current law or grant publication clearance. Compatible classes with unknown evidence are not positive identifications. Fully witnessed classes satisfy only the declared positive requirements.

Missing required fields, unknown fields, wrong types and violated rules return input issues. Numeric values and outputs must be finite. Lists and matrices must be dense, without missing cells. Numeric lists allow at most 10000 entries; ordinary string lists allow at most 128 strings of 128 UTF-16 units each; numeric matrices allow at most 128 rows and 128 columns, subject to narrower requirements above.

Alternative or Complementary methods

For a related step, use Off Record on Background Attribution Tier Lookup: On-record, background and off-record terms depend on an agreement about use and attribution. For a complementary comparison, use Deepfake Authenticity Verification Escalation Checker: Authenticity escalation uses reviewed provenance and consistency evidence to decide which checks remain necessary.

References

Anonymous Source Justification Editorial Checklist — tool.io

Similar or alternative tools

Off Record on Background Attribution Tier Lookup
On-record, background and off-record terms depend on an agreement about use and attribution.
Deepfake Authenticity Verification Escalation Checker
Authenticity escalation uses reviewed provenance and consistency evidence to decide which checks remain necessary.