{"id":"W1966130221","doi":"10.5539/gjhs.v7n4p392","title":"Prediction of Breast Cancer Survival Through Knowledge Discovery in Databases","year":2015,"lang":"en","type":"article","venue":"Global Journal of Health Science","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Iran University of Medical Sciences","keywords":"Breast cancer; Context (archaeology); Medicine; IBM; Predictive modelling; Cancer; Oncology; Machine learning; Computer science; Internal medicine; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006783837,0.0001310313,0.0004954122,0.0001669959,0.0004155821,0.00001224925,0.0005914698,0.00006891093,0.00003220601],"category_scores_gemma":[0.0006640569,0.0001036589,0.0000507067,0.001673646,0.0005283697,0.001839779,0.0001986964,0.0005594192,0.00001960595],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002334902,"about_ca_system_score_gemma":0.01777587,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02543286,"about_ca_topic_score_gemma":0.009022286,"domain_scores_codex":[0.9954712,0.0005559662,0.001942944,0.0002574479,0.001000574,0.0007718888],"domain_scores_gemma":[0.9960694,0.0001915309,0.001372118,0.0002800899,0.001674232,0.000412675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001610807,0.0001332263,0.9844974,0.000220097,0.000003325791,0.000004780762,0.002195284,0.0002444264,0.00004343655,0.003925653,0.002371601,0.006199711],"study_design_scores_gemma":[0.0005857887,0.0003407571,0.966809,0.002612993,0.000008432236,0.00009247535,0.02293644,0.0007512508,0.00008602609,0.002863726,0.00278525,0.0001278427],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980014,0.003668857,0.001436736,0.004672391,0.007673278,0.0004644481,0.000632008,0.00001552554,0.001422727],"genre_scores_gemma":[0.9977322,0.0007488997,0.0006590833,0.0003644974,0.0004562696,0.000007558323,0.000002298635,0.000006622878,0.00002259234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02074115,"threshold_uncertainty_score":0.9877924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4373148152868181,"score_gpt":0.5608005764447357,"score_spread":0.1234857611579176,"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."}}