{"id":"W2797542577","doi":"10.1016/j.cell.2018.03.043","title":"Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal","year":2018,"lang":"en","type":"article","venue":"Cell","topic":"Renal cell carcinoma treatment","field":"Medicine","cited_by":671,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Biomedical Research Council; Seventh Framework Programme; CRUK Lung Cancer Centre of Excellence; Nemzeti Kutatási Fejlesztési és Innovációs Hivatal; Ministerio de Economía y Competitividad; Rosetrees Trust; National Institute for Health and Care Research; Medical Research Council; Celgene; Institute of Cancer Research; UCLH Biomedical Research Centre; Novo Nordisk Fonden; Cancer Research UK; Francis Crick Institute; Wellcome Trust; Kræftens Bekæmpelse; AstraZeneca; Royal Marsden Cancer Charity; NIHR Maudsley Biomedical Research Centre; GlaxoSmithKline; Pfizer","keywords":"Biology; Clear cell renal cell carcinoma; Somatic evolution in cancer; Evolutionary biology; Renal cell carcinoma; Evolutionary dynamics; Genetics; Bioinformatics; Gene; Oncology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000602444,0.0001121913,0.0003268035,0.0003345735,0.0002415856,0.0005008299,0.0002085754,0.000230898,0.0007345908],"category_scores_gemma":[0.002060282,0.0001074864,0.0001715305,0.0004229497,0.0002644518,0.0001770687,0.000287733,0.0001836784,0.00007353908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005102574,"about_ca_system_score_gemma":0.0003297969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004083099,"about_ca_topic_score_gemma":0.006187589,"domain_scores_codex":[0.9997728,0.0001058957,0.00000828679,0.00005628223,0.00002409665,0.00003258521],"domain_scores_gemma":[0.9990408,0.000506469,0.000239978,0.00008073435,0.00004847229,0.00008356727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007612066,0.00003019302,0.9612011,0.00003838848,0.0001055981,0.0004526637,0.0002978549,0.005107977,0.02028761,0.0005748585,0.0001113465,0.01103119],"study_design_scores_gemma":[0.00003169846,0.0003094844,0.9586897,0.00001066649,0.00008185464,0.002073383,0.0003595643,0.02846782,0.007551688,0.0008911255,0.001514777,0.00001837255],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990558,0.0001776488,0.0006106901,0.00001014428,6.962164e-7,0.000002912717,0.00005529888,0.000004619775,0.00008212147],"genre_scores_gemma":[0.9994615,0.00003744822,0.000313394,0.000003544138,7.652654e-7,0.000002590198,0.0001016077,0.000002283959,0.00007698574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004083099,"threshold_uncertainty_score":0.008118689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01420107624236307,"score_gpt":0.2375536320177146,"score_spread":0.2233525557753515,"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."}}