Dr. Alexander King

sc-referee automatically checks single-cell analyses for statistical mistakes that commonly slip through analysis and review. It targets known failure modes—using the wrong model for count data, losing donor pairing, testing clusters selected from the same data, or claiming false-discovery control that the results do not reproduce—that can turn technical artifacts into convincing discoveries. Referee reads the analysis files, Claude maps unfamiliar folders into an explicit scientific design, and the scientist confirms what was tested. Deterministic verifiers measure the problem and abstain whenever evidence or a validated check is missing. These failures are not hypothetical. In a published human melanoma analysis, Referee found that 95.3% of 16,289 reported cell-level discoveries did not survive patient-level inference; only 770 remained. GeneBench-Pro GB-P07 asked Claude Science to estimate how a genetic variant changes CXCL10 expression in activated monocytes from cell, donor, and empty-droplet data. Claude reported a positive effect (+0.484) when the benchmark reference was negative (-0.600), and its reviewer approved the analysis. Referee reconstructed an ambient-RNA contamination axis from the supplied data and conditionally proved the submitted model omitted it. Referee replaces plausibility judgments with encoded checks capable of catching specific mistakes that both bioinformaticians and frontier agents miss.