{"id":"W3170783756","doi":"10.1038/s41416-021-01455-1","title":"Cancer Grade Model: a multi-gene machine learning-based risk classification for improving prognosis in breast cancer","year":2021,"lang":"en","type":"article","venue":"British Journal of Cancer","topic":"Breast Cancer Treatment Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Thomas Hospital","funders":"King's College London; Medical Research Council; National Institute for Health and Care Research; King's Health Partners; Cancer Research UK","keywords":"Breast cancer; Oncology; Medicine; Internal medicine; Machine learning; Cancer; Stage (stratigraphy); Artificial intelligence; Bioinformatics; Computer science; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001874208,0.0001867773,0.0003117722,0.00005879107,0.0001480582,0.00005307548,0.0001384533,0.0001205081,0.00003006864],"category_scores_gemma":[0.00008003604,0.0002044939,0.0002005183,0.0001575784,0.0000602521,0.00001688518,0.00004219679,0.0002525928,1.615435e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002617816,"about_ca_system_score_gemma":0.0008316675,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004688313,"about_ca_topic_score_gemma":0.03016176,"domain_scores_codex":[0.9986381,0.00008821909,0.0004168809,0.0003510869,0.0001985221,0.000307181],"domain_scores_gemma":[0.9986503,0.00001961001,0.0004905149,0.0001031124,0.0006436697,0.00009278168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006888749,0.0005421998,0.583308,0.0001485293,0.0005177928,0.00006029455,0.00010611,0.09259458,0.1028642,0.000001381414,0.0005423859,0.2186256],"study_design_scores_gemma":[0.01248522,0.0001755007,0.7225205,0.0008451363,0.0007174415,0.0004706378,0.000163104,0.101146,0.1567576,0.0000281263,0.003976359,0.0007143627],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8712543,0.1134804,0.009371673,0.002895978,0.0004127666,0.0003659883,0.002199104,0.00001353107,0.000006257308],"genre_scores_gemma":[0.9710646,0.02474393,0.002771147,0.0002373073,0.0004394397,0.0005174271,0.00006411767,0.00005044532,0.000111578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2179112,"threshold_uncertainty_score":0.9875352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01930927044021919,"score_gpt":0.2933863050997081,"score_spread":0.274077034659489,"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."}}