Assessing Scientific Claims in Agentic Workflows: MAER and GAVEL-X for Biomedical Research Evidence

An acceptable biomedical-agent answer does not by itself establish what its evidence justifies. This paper develops Multi-Agent Ecosystem Risk (MAER) and GAVEL-X (Governance and Audit for Verified, explainable LLM systems) for evidence-qualified research handoffs. MAER specifies interaction-specific evidence obligations; GAVEL-X binds judgments to executions, scientific contracts, claim purposes, sources, and revisions. Typed transitions distinguish evidence recovery, contract revision, new computation, claim revision, and evaluator change. A retrospective audit finds 52 versus 45 interjudge acceptance disagreements among 350 matched backend–task keys in two BiomniBench-AI4S score representations; neither count estimates biological error. In 48 scripted workflows, all four deterministic procedure/presentation arms resolve 168 of 240 claim–view pairs and withhold on 72. Budgeted evidence recovery resolves all 24 eligible cases but ties a competent dependency checklist. These are finite conformance results, not superior assessment or biomedical assurance. The camera-ready adds exploratory language-model studies from one family. On 72 unresolved views, an obligation checklist increases appropriate abstention, while GAVEL-X presentation shows no positive estimate; resolvable views were not run, so useful resolution and unnecessary withholding remain unmeasured in that arm. On twenty agent self-reports, checklist verdicts agree with an author-defined reference in 40/40 assessments, compared with 70–80% for generic review. The reference depends on an unverified sample-label-swap hypothesis. A separate thirty-trace raw-log study does not reproduce this performance; it is not a paired record-format comparison. In ten live relay workflows, six analysis agents perform a data-level check after challenger questions, without changing the reported count; no causal effect is identified. The contribution is claim-centered methodology and bounded component evidence. Human benefit, six-family validity, integrated model-informed investigation, and discovery acceleration remain unestablished.