{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000207695,0.00009415625,0.00008325149,0.00009579848,0.0000839865,0.00002177354,0.00009265439,0.00008928902,0.000003340815],"category_scores_gemma":[0.00003635713,0.00009604787,0.00004451106,0.0001631922,0.00001942462,0.000005919111,0.00002916377,0.00003885824,0.000002705858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000401099,"about_ca_system_score_gemma":0.00007384002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006560276,"about_ca_topic_score_gemma":0.00006223587,"domain_scores_codex":[0.9991825,0.00001909308,0.0001833144,0.0003122835,0.00006988332,0.000232903],"domain_scores_gemma":[0.9996021,0.00001313104,0.00008436622,0.0001580094,0.00009147924,0.00005085028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001915299,0.00003449441,0.001589068,0.00003214937,0.00003546173,1.634495e-7,0.0001257187,0.0181741,0.9190205,0.00002721144,0.003284619,0.05748495],"study_design_scores_gemma":[0.001221921,0.000032814,0.00386376,0.000009854391,0.00001321714,9.234619e-7,0.0001242059,0.9441811,0.03821938,0.0001482683,0.0120399,0.0001446281],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4277244,0.00153194,0.5625143,0.002761154,0.0009445443,0.002126473,0.002195409,0.000136359,0.0000654102],"genre_scores_gemma":[0.9861425,0.00199585,0.004667443,0.0001150991,0.0001585037,0.001329863,0.002305384,0.00004766105,0.003237733],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.926007,"threshold_uncertainty_score":0.3916719,"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."}}