{"id":"W4386526126","doi":"10.3390/genes14091768","title":"Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine Learning","year":2023,"lang":"en","type":"article","venue":"Genes","topic":"Breast Cancer Treatment Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; York University; University of Toronto; Sunnybrook Health Science Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Terry Fox Research Institute","keywords":"Medicine; Anthracycline; Bone metastasis; Oncology; Internal medicine; Breast cancer; Brain metastasis; Metastasis; Odds ratio; Multivariate analysis; Estrogen receptor; Cancer; Chemotherapy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00006850147,0.0001269296,0.0001603759,0.00005601594,0.00007455759,0.000005504949,0.00007133884,0.00004245076,0.000007086172],"category_scores_gemma":[0.000006054247,0.0001103632,0.0000914537,0.0001446379,0.00002758024,0.000004209272,0.00008929027,0.00004437708,5.292464e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003565072,"about_ca_system_score_gemma":0.00003109632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002411698,"about_ca_topic_score_gemma":0.0006604416,"domain_scores_codex":[0.9992009,0.00004878788,0.0001702661,0.0002371357,0.0001417379,0.0002011422],"domain_scores_gemma":[0.9997451,0.00001065254,0.00007862417,0.00009974597,0.00004003166,0.0000257945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009271871,0.00005254786,0.9632041,0.00001521922,0.0001952708,0.000004270591,0.0001916682,0.001332188,0.02108179,7.454136e-7,0.000007950938,0.01382152],"study_design_scores_gemma":[0.001679327,0.0000786841,0.9647458,0.00009959607,0.00004747354,0.000005463223,0.0005960906,0.001250309,0.03080092,0.000007101098,0.0004959931,0.0001932798],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970835,0.002269178,0.0001343568,0.000103844,0.0001457272,0.00008713588,0.0001589208,0.00001352007,0.000003774541],"genre_scores_gemma":[0.9982135,0.001396127,0.00005297365,0.00002756463,0.00007269214,0.00002768182,0.0001734945,0.00002161486,0.00001434612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01362824,"threshold_uncertainty_score":0.450048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0216102140976687,"score_gpt":0.280373529287209,"score_spread":0.2587633151895403,"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."}}