{"id":"W4412163735","doi":"10.1158/1557-3265.aimachine-a003","title":"Abstract A003: An active learning platform for predictive oncology in rare cancers","year":2025,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Oncology; Precision oncology; Internal medicine; Clinical Oncology; Cancer; Cancer research","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002221664,0.001116633,0.0007780982,0.0009995222,0.0003683088,0.001666536,0.002240725,0.001590693,0.01871901],"category_scores_gemma":[0.005199604,0.0005339142,0.001149202,0.0005102085,0.0006048794,0.001329994,0.002033226,0.002665139,0.005893798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005277424,"about_ca_system_score_gemma":0.0008530563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001331622,"about_ca_topic_score_gemma":0.001458753,"domain_scores_codex":[0.9992532,0.0002420198,0.00004173343,0.0001563769,0.0002688139,0.00003782831],"domain_scores_gemma":[0.998172,0.001198254,0.00009473484,0.0001526289,0.0002389291,0.0001433791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001353661,0.000495751,0.002687847,0.0006176349,0.0002935578,0.000411388,0.0001304165,0.3625955,0.0190045,0.0308409,0.1095039,0.4720649],"study_design_scores_gemma":[0.00009631463,0.0001289648,0.0001831009,0.00002411683,0.00002043073,0.00004242423,0.000008417403,0.9617348,0.003612614,0.02131322,0.01280988,0.00002567492],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.007556805,0.0009061089,0.9353301,0.001422679,0.0004814847,0.0002214613,0.002674475,0.04554344,0.00586352],"genre_scores_gemma":[0.305139,0.001641572,0.6541219,0.002124072,0.0006629072,0.001799854,0.01095498,0.003288847,0.02026685],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01871901,"threshold_uncertainty_score":0.06262136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1482777133428529,"score_gpt":0.5362465280913922,"score_spread":0.3879688147485393,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}