{"id":"W2139782977","doi":"10.1007/s10549-006-9400-z","title":"MR-determined metabolic phenotype of breast cancer in prediction of lymphatic spread, grade, and hormone status","year":2006,"lang":"en","type":"article","venue":"Breast Cancer Research and Treatment","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":130,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kingston Health Sciences Centre","funders":"","keywords":"Breast cancer; Multivariate statistics; Multivariate analysis; Internal medicine; Principal component analysis; Oncology; Magnetic resonance imaging; Medicine; Cancer; Radiology; Artificial intelligence; Mathematics; Statistics; Computer science","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":[0.0001926929,0.0002094675,0.0005578066,0.0003866676,0.00005439169,0.00001536989,0.00005527032,0.00007944116,0.0001588146],"category_scores_gemma":[0.000006591548,0.0001624466,0.00005200808,0.0005286779,0.000343771,0.0001122976,0.0000496153,0.00009652715,0.000001078744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005928855,"about_ca_system_score_gemma":0.0005299335,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1102577,"about_ca_topic_score_gemma":0.006447841,"domain_scores_codex":[0.9980456,0.00008900536,0.0003919025,0.0004010796,0.0005525718,0.0005198886],"domain_scores_gemma":[0.9989953,0.0001208337,0.0001081014,0.000280136,0.0002626937,0.0002329242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00261405,0.001404524,0.8810015,0.0003002986,0.0003092761,0.00003570312,0.0003532052,0.00002731016,0.01350873,0.000154305,0.0003895604,0.0999015],"study_design_scores_gemma":[0.007360603,0.0007337074,0.983702,0.0003825267,0.0001904771,0.00007321091,0.0001140364,0.0001649486,0.006684657,0.000177911,0.0003212021,0.00009473426],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9650395,0.02939362,0.000002025843,0.001677186,0.00004590798,0.0009044554,0.002699013,0.0000159054,0.0002224014],"genre_scores_gemma":[0.9463056,0.05252374,0.00007490359,0.0000109699,0.0001685319,0.0006600096,0.00003700946,0.00002765205,0.0001915922],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1038099,"threshold_uncertainty_score":0.8956671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04010344188028359,"score_gpt":0.3467171388943818,"score_spread":0.3066136970140982,"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."}}