Claims

Records, Observables, and Origins describe and classify an observation. Claims are how the standard records who said so. Every evaluative statement — "this showed instantaneous acceleration," "this is best explained by an unknown craft" — is a claim: an attributed assertion with a rationale and pointers to the specific evidence that backs it.

What every claim carries

Every claim, whatever it's about, shares the same structure from @disclosureos/records/shared: an attribution (who evaluated it, when, why) plus the in-record evidence references that justify it.

import { evidenceRef, type Claim } from '@disclosureos/records/shared';

// who / when / why + the evidence that backs the call
{
  evaluatedBy: 'Scientific Coalition for UAP Studies',
  evaluatedAt: '2026-03-01T00:00:00Z',
  rationale: 'Radar tracked descent from ~80,000 ft to sea level in seconds.',
  evidenceRefs: [evidenceRef('sensor', 'princeton-spy1-radar')],
}

The point of this structure is auditability: a claim without evidenceRefs is an opinion; a claim with them can be traced back to the exact sensor reading, testimony, or document in the record that supports it.

Evidence references

An evidence reference is a typed string — <kind>:<id> — pointing at something that already lives in the record. There are four kinds:

evidenceRef('sensor', 'princeton-spy1-radar'); // → 'sensor:princeton-spy1-radar'

The evidence must exist in the record first, with a stable id. The CLI and parseEnrichedObservation warn when a claim cites an evidence reference that doesn't resolve.

The two claim shapes

Two first-party shapes extend that shared structure, one per evaluative layer:

import { createObservableClaim } from '@disclosureos/observables';
import { createOriginClaim } from '@disclosureos/origins';

const observableClaim = createObservableClaim('measured', {
  confidence: 0.7,
  rationale: 'Doppler velocity profile shows acceleration inconsistent with known aircraft.',
  evidenceRefs: [evidenceRef('sensor', 'princeton-spy1-radar')],
  evaluatedBy: 'example-institution',
});

const originClaim = createOriginClaim('1.1.3', 0.4, {
  rationale: 'Performance exceeds known aerospace capability.',
  alternativeHypotheses: [{ nodeId: '1.1.1.2.1', confidence: 0.25, label: 'Classified program' }],
  evidenceRefs: [evidenceRef('sensor', 'princeton-spy1-radar')],
});

Where claims live: the two slots

The evaluative slots that Observables and Origins add to an Observation each hold a list of claims, never a single value:

Holding lists is deliberate. It lets the record keep two distinct kinds of uncertainty straight.

Two axes of uncertainty

Inter-claim: evaluators disagree

When two institutions assess the same case differently, both claims sit in the slot side by side. Neither overwrites the other.

// instantaneous_acceleration, as assessed by two parties
[
  createObservableClaim('measured', {
    confidence: 0.85,
    rationale: 'Radar tracked descent from ~80,000 ft to sea level in seconds.',
    evaluatedBy: 'Navy aviator (firsthand)',
  }),
  createObservableClaim('not_indicated', {
    confidence: 0.6,
    rationale: 'Available sensor data judged insufficient to establish the maneuver.',
    evaluatedBy: 'AARO (later review)',
  }),
]

The disagreement is the data. Scoring reads it and sets a contested flag when claims disagree in direction — it never averages the dispute away.

Intra-claim: one evaluator hedges

A single origin claim can carry a primary hypothesis alongside weighted alternatives — one evaluator expressing their own internal uncertainty:

createOriginClaim('1.1.3', 0.4, {
  rationale: 'Best fit given the kinematics, but data is incomplete.',
  alternativeHypotheses: [{ nodeId: '1.1.1.2.1', confidence: 0.25, label: 'Classified program' }],
});

These two axes are kept distinct on purpose: a list of claims is disagreement between evaluators; primaryHypothesis + alternativeHypotheses is one evaluator's own hedging.

Working with claims

• Claiming Observables — the discipline for picking the observable, level, and confidence, and citing evidence.
• Claiming Origins — choosing OCS nodes and expressing alternatives honestly.
• Compellingness — how claims and their evidence become a score, and how contested is derived.