{"id":"W4410640732","doi":"10.1007/978-3-031-84539-0_7","title":"Precision Medicine Beyond Genomics","year":2025,"lang":"en","type":"book-chapter","venue":"","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network; University of Toronto","funders":"","keywords":"Genomics; Precision medicine; Computational biology; Biology; Data science; Computer science; Genetics; Genome; Gene","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":[0.01403622,0.001186094,0.002101025,0.002437104,0.001283518,0.00740567,0.001786834,0.005389069,0.01308359],"category_scores_gemma":[0.02037731,0.0004970858,0.00140982,0.001234988,0.008991243,0.006831007,0.005403217,0.008958337,0.005582514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003928434,"about_ca_system_score_gemma":0.004478159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001855219,"about_ca_topic_score_gemma":0.0007936796,"domain_scores_codex":[0.9924051,0.003740221,0.0003900123,0.001224207,0.001878199,0.0003621902],"domain_scores_gemma":[0.9793153,0.0125639,0.0009699311,0.003405394,0.002760799,0.0009847394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001786407,0.0000827897,0.002082817,0.002425796,0.0004526363,0.0005134614,0.0006547559,0.002457478,0.002994584,0.518831,0.1203081,0.3490179],"study_design_scores_gemma":[0.00004066954,0.0001354534,0.0007918471,0.00151124,0.00009298996,0.0005016985,0.0002505827,0.001283458,0.001151864,0.5859337,0.4082349,0.00007157667],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.004557416,0.3461146,0.1544359,0.3783759,0.02063196,0.000213572,0.001884789,0.002232073,0.09155361],"genre_scores_gemma":[0.2657786,0.3244015,0.1262297,0.1983286,0.04379511,0.0007331861,0.002338868,0.0009235857,0.03747103],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01403622,"threshold_uncertainty_score":0.07423151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008181108084202797,"score_gpt":0.2397127075137981,"score_spread":0.2315315994295953,"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."}}