{"id":"W2401611683","doi":"10.1158/2159-8290.cd-nd2012-007","title":"Breast Cancer Screening Goes Personalized","year":2012,"lang":"en","type":"article","venue":"Cancer Discovery","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cancer; Computational biology; Breast cancer; Medicine; Bioinformatics; Computer science; Biology; Internal medicine","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":[0.004734512,0.0008006304,0.001103232,0.001864248,0.002150134,0.006395319,0.001209263,0.005547094,0.05333142],"category_scores_gemma":[0.01778104,0.000722927,0.001214031,0.001328167,0.00468005,0.007845452,0.004935624,0.01013972,0.03087163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002826927,"about_ca_system_score_gemma":0.003575283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005820109,"about_ca_topic_score_gemma":0.007166778,"domain_scores_codex":[0.9951819,0.001283104,0.0002572961,0.0007938098,0.002046996,0.0004368612],"domain_scores_gemma":[0.9939375,0.002014536,0.0003831336,0.001642311,0.001380874,0.0006416097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001523021,0.0001262138,0.003240008,0.0009055653,0.0002374248,0.0001915212,0.001001957,0.0004526477,0.0009145942,0.1196133,0.4870004,0.3861639],"study_design_scores_gemma":[0.00004074107,0.00008019603,0.002197022,0.0008116718,0.0001004789,0.000392204,0.0002713041,0.0001546163,0.0004057254,0.06267451,0.9328216,0.00004992328],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.006458953,0.07888266,0.01926752,0.6162684,0.02519558,0.0001677264,0.003986269,0.002423087,0.2473498],"genre_scores_gemma":[0.1566265,0.1364602,0.02431902,0.4722544,0.03126993,0.0003703387,0.004488415,0.00129558,0.1729156],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05333142,"threshold_uncertainty_score":0.1784114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01468920328017518,"score_gpt":0.2792943442795908,"score_spread":0.2646051409994156,"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."}}