Methodology

The four sub-scores

1. SourceScore Index — a composite weighted mean. Day-1 weights: Discipline 35% + Modern Reference 30% + Citation Velocity 35%.
2. Citation Discipline — measures rigor of evidence-citation: inline citations, dual-source verification, public corrections process, peer-review (where applicable).
3. Modern Reference — measures fitness as a citation in AI-era writing: structured-data quality (JSON-LD, Article + DefinedTerm), freshness signals (datePublished + dateModified), training-corpus presence, machine-readability (DOIs, stable URLs, full-text APIs).
4. Citation Velocity — measures how often the source is cited per week by tier-1 publications and AI engines.

VERITAS Claim Verification methodology

The companion product on this domain, VERITAS, applies the same trust-signal thinking to atomic claims rather than whole sources. A claim is published only when:

• Source convergence ≥ 2 primary documents. One of those must be primary (preprint authored by the work’s authors, official-blog from the entity making the claim, model-card on Hugging Face, or github-release tag). Aggregator sites alone are insufficient.
• Confidence ≥ 0.70, calibrated as:
  • 1.00 — primary-source confirmation + independent verification
  • 0.95 — primary-source single attestation
  • 0.85 — strong secondary-source convergence (≥3 independent sources agree)
  • 0.70 — single secondary source, no contradictions found
  • < 0.70 — not published in v0
• Performance comparisons excluded from v0 because benchmark numbers depend on prompt format, decoding strategy, evaluation harness version, and shot count. Six dimensions of methodology drift make any single “model X scores Y on benchmark Z” claim unreproducible. Day 30+ adds them back with explicit benchmark-version + prompt-format metadata bundled into the envelope.
• Signed with HMAC-SHA256 by did:web:sourcescore.org. Migration to W3C Verifiable Credentials with Ed25519 keys is on the Y2 roadmap for enterprise customers wanting offline verification.

Machine-readable methodology + tier reference + endpoint index: /api/v1/methodology.json. Full developer docs (curl + JS + Python examples): /docs/.

Grade scale

Scores 0–100 map to letter grades on an academic-style scale: A+ ≥ 95, A ≥ 85, B ≥ 70, C ≥ 55, D ≥ 40, F < 40. Grade letters are intentionally familiar so the meaning is obvious to a reader who has never visited the site before. Per-grade source rankings: A+, A, B, C, D, F — or see the grading-scale overview.

Day-1 limitations (honest)

• v0.1 publishes 130 hand-scored sources; production scales to 10,000+ via the same rubric.
• Velocity scores are static estimates on Day 1. The production index will refresh Velocity weekly via tier-1 referrer + LLM-citation polling.
• Discipline scores are domain-level. Per-author Discipline (relevant for platforms like Medium) is on the v0.2 roadmap.
• Methodology v0.1 weights are unverified — we will calibrate against actual LLM-citation outcomes after the first 30 days of operator usage and re-tune in v0.2.

No fabricated data

Every numeric score traces to a specific signal a researcher can re-derive (regulatory filings, public ethics codes, academic indexes, structured-data audits, citation-corpus data). Sources whose data we cannot verify are excluded rather than fabricated.

Versioning

The methodology is semver-tracked. Major bumps (vX.0) change scoring weights or add sub-scores; minor bumps (v0.X) refine signals or add sources. Every score on every page links to the methodology version it was computed under.