{"id":"W4390347126","doi":"10.3390/a17010013","title":"Machine Learning Model for Multiomics Biomarkers Identification for Menopause Status in Breast Cancer","year":2023,"lang":"en","type":"article","venue":"Algorithms","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Breast cancer; Computer science; Artificial intelligence; Cancer; Machine learning; Medicine; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001311781,0.000587258,0.0007455621,0.0008703147,0.0004026533,0.000829356,0.001075213,0.001015238,0.001983608],"category_scores_gemma":[0.00191709,0.0002069305,0.0008720563,0.0006166171,0.0003473813,0.0004818288,0.0005360924,0.001267951,0.0006089685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008915676,"about_ca_system_score_gemma":0.001156097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009661329,"about_ca_topic_score_gemma":0.006386917,"domain_scores_codex":[0.9996176,0.0001266132,0.00002361633,0.0001117043,0.00006284853,0.00005763908],"domain_scores_gemma":[0.9994948,0.0003004631,0.00005351695,0.00002314242,0.0001133925,0.00001464451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001682854,0.000166843,0.009783541,0.00009906931,0.0001535234,0.0001825581,0.0001081995,0.8719931,0.001940909,0.01051685,0.00301085,0.1018763],"study_design_scores_gemma":[0.000003651133,0.00001479026,0.0005843223,0.000005058458,0.000009789938,0.00001356011,0.000005437968,0.9969944,0.0001487232,0.001940413,0.0002757035,0.000004216652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07141282,0.001178616,0.9212525,0.001411262,0.000116242,0.0001267997,0.0006273406,0.0008725782,0.00300172],"genre_scores_gemma":[0.8989491,0.000709522,0.0913277,0.0003474707,0.0001284447,0.0005677551,0.001128624,0.00004342198,0.006797923],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009661329,"threshold_uncertainty_score":0.01921016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02372530065933746,"score_gpt":0.3120450289008868,"score_spread":0.2883197282415493,"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."}}