{"id":"W2982154804","doi":"10.1093/molbev/msz242","title":"Molecular Biology and Evolution of Cancer: From Discovery to Action","year":2019,"lang":"en","type":"article","venue":"Molecular Biology and Evolution","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Institute of Cancer Research; Ontario Institute for Cancer Research","funders":"U.S. National Library of Medicine; National Institute on Aging; Yale School of Public Health, Yale University; National Cancer Institute; National Institutes of Health; Cancer Research UK; Notsew Orm Sands Foundation; Yale University","keywords":"Biology; Action (physics); Cancer; Process (computing); Ecological niche; Cognitive science; Suite; Niche construction; Computational biology; Evolutionary biology; Ecology; Computer science; Genetics","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":[0.0001027261,0.000177404,0.0002258635,0.00009059087,0.00005164054,0.00001290974,0.00009866102,0.0003164247,0.000007914737],"category_scores_gemma":[0.00006857933,0.0001806869,0.00006406608,0.00009833091,0.0001319936,0.000008141442,0.0001754377,0.00008533835,0.000005192053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006528632,"about_ca_system_score_gemma":0.00008949253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001675923,"about_ca_topic_score_gemma":0.0002884058,"domain_scores_codex":[0.9988976,0.00008468814,0.0002149297,0.0005169951,0.00004747515,0.0002382754],"domain_scores_gemma":[0.9994333,0.0000211586,0.0001071846,0.0002824772,0.00007319545,0.00008264939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001584446,0.00002289261,0.1451752,0.00001422822,0.00007312863,6.565846e-7,0.00001377242,0.0002453632,0.8427734,0.01002531,0.00004475291,0.001452885],"study_design_scores_gemma":[0.001672299,0.001517857,0.2402517,0.00005880004,0.0001540509,0.00001161257,0.0001406142,0.0005077935,0.7294525,0.02002945,0.005581545,0.0006218427],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9100765,0.01057989,0.07819806,0.000239839,0.0003564149,0.0002556449,0.0001910049,0.000008093974,0.00009455437],"genre_scores_gemma":[0.9979276,0.0007911975,0.0005997932,0.0002450824,0.0001060138,0.00003124457,0.0002439521,0.00001721654,0.0000378797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1133209,"threshold_uncertainty_score":0.7368199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004469765112738821,"score_gpt":0.2648532402534113,"score_spread":0.2603834751406725,"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."}}