{"id":"W4397011101","doi":"10.20944/preprints202405.0996.v1","title":"Identifying Robust Biomarker Panels for Breast Cancer Screening","year":2024,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Manitoba","funders":"","keywords":"Biomarker; Breast cancer; Cancer; Oncology; Medicine; Internal medicine; Biology; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004699726,0.001116387,0.001668328,0.002709463,0.000343372,0.001632728,0.0005850794,0.001084129,0.001480133],"category_scores_gemma":[0.009493378,0.0004348073,0.0008266687,0.001714677,0.0003222576,0.0009045067,0.0008812156,0.0009223075,0.00138303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004155289,"about_ca_system_score_gemma":0.0008400221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006410042,"about_ca_topic_score_gemma":0.0008138686,"domain_scores_codex":[0.9977632,0.001069587,0.0001315511,0.0003945168,0.0004787805,0.0001624566],"domain_scores_gemma":[0.998015,0.0007850107,0.0003211646,0.0003166982,0.0004878953,0.00007421874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001769926,0.0006412683,0.1308673,0.0006718261,0.0007901836,0.0005397111,0.0001217473,0.07082728,0.2065415,0.003371384,0.008966985,0.5748909],"study_design_scores_gemma":[0.0002011175,0.001178306,0.1138733,0.0002690164,0.0007553939,0.0007611841,0.0001924973,0.6736742,0.161544,0.02789412,0.01946163,0.0001952274],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3100812,0.01171853,0.6598742,0.00205091,0.0003411194,0.0006833318,0.006343134,0.005133924,0.003773564],"genre_scores_gemma":[0.7149132,0.001975968,0.2766267,0.0004708722,0.0001829193,0.0003824897,0.004196249,0.0001368643,0.001114738],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004699726,"threshold_uncertainty_score":0.02485478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2175030746545123,"score_gpt":0.396964903092244,"score_spread":0.1794618284377317,"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."}}