Corrections, evidence, and commercial independence

Sources and identity

OpenGPT preserves the publisher's model name or ID and configuration. An official model ID is added only when provider documentation supports the exact mapping. Source records that cannot be safely mapped remain visible as source records rather than being assigned an invented identity.

Ranking and comparison

Ranks remain scoped to the named source, metric, snapshot, benchmark version, and comparable configuration group. OpenGPT does not create a universal Agent score across incompatible benchmarks. Costs, latency, repeat-run evidence, and intervention are shown only when the source reports comparable values.

Submission and review

A user submission first enters editorial review. A reviewer may approve or reject the evidence record. An administrator may separately publish an approved candidate record. Catalog inclusion, identity mapping, comparison eligibility, and leaderboard changes remain separate operations and require their own evidence.

• Submitters cannot choose rank, trust grade, comparability, or publication status.
• Review decisions should record the evidence checked and the reason.
• Public candidate records are not endorsements or rankings.

Corrections and appeals

Send corrections to contact@opengpt.com with the affected URL, the exact statement or identity mapping at issue, a public source, and a concise explanation. OpenGPT may correct labels, links, mappings, dates, or evidence status; preserve an audit trail where the workflow supports it; and withdraw a candidate record while a dispute is reviewed.

Commercial independence

OpenGPT does not sell rank, trust grade, review approval, comparison eligibility, or recommendation labels. Sponsorship or commercial support, if introduced, must be clearly disclosed and cannot alter scoring rules, source selection, evidence thresholds, correction handling, or editorial placement.

Conflicts and limitations

Provider reports and submitter relationships are evidence context, not automatic disqualification or validation. OpenGPT labels the available evidence and keeps uncertainty, small samples, conflicting results, and unreported fields visible.