{"id":"W4318919835","doi":"10.1016/s1470-2045(23)00007-4","title":"Accelerating cancer omics and precision oncology in health care and research: a Lancet Oncology Commission","year":2023,"lang":"en","type":"article","venue":"The Lancet Oncology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Institute for Cancer Research","funders":"Cancer Research UK; World Health Organization","keywords":"Precision oncology; Omics; Clinical Oncology; Medicine; Cancer; Oncology; Precision medicine; Molecular oncology; Bioinformatics; Internal medicine; Computational biology; Biology; Pathology","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":[0.1131765,0.003678857,0.006688377,0.003559472,0.004762056,0.019289,0.005566181,0.06511568,0.01148602],"category_scores_gemma":[0.158296,0.002243565,0.003960071,0.003801114,0.01845915,0.02948833,0.01377342,0.06977109,0.005793412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01504872,"about_ca_system_score_gemma":0.05099553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0126513,"about_ca_topic_score_gemma":0.01415156,"domain_scores_codex":[0.9530451,0.01653754,0.003121065,0.004796768,0.01828413,0.004215376],"domain_scores_gemma":[0.7547019,0.140475,0.006485759,0.01004666,0.03754115,0.05074948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001203169,0.0000674784,0.0001457557,0.0003635543,0.0001140705,0.0001026523,0.0002079851,0.0002272976,0.0001453334,0.03193092,0.9379491,0.02862548],"study_design_scores_gemma":[0.0004018006,0.0001102482,0.0003404922,0.001755437,0.0001270819,0.000141449,0.0003027664,0.0003204863,0.0001184984,0.1004899,0.8957658,0.0001260355],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.0001071648,0.07108471,0.0009332306,0.8595546,0.06593469,0.00002449805,0.0001022604,0.00008097145,0.002177977],"genre_scores_gemma":[0.006139297,0.07315616,0.004251805,0.8023137,0.1073731,0.0001638941,0.000160628,0.0001937828,0.006247638],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.1131765,"threshold_uncertainty_score":0.5985416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.164067860684152,"score_gpt":0.4647747784755713,"score_spread":0.3007069177914193,"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."}}