{"id":"W3049682127","doi":"10.1158/1538-7445.am2020-sy09-03","title":"Abstract SY09-03: PROFYLEing Cancer for KiCS: The Canadian Pediatric Precision Oncology Initiative","year":2020,"lang":"en","type":"article","venue":"Cancer Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; Alberta Children's Hospital; Hospital for Sick Children; Children's Hospital of Eastern Ontario; Montreal Children's Hospital; BC Cancer Agency","funders":"","keywords":"Cancer; Medicine; Citation; Pediatric oncology; Pediatric cancer; Gerontology; Oncology; Internal medicine; Family medicine; Library science; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.006515391,0.0009250257,0.0004902855,0.002483337,0.00711826,0.006640676,0.003266398,0.003348706,0.06788415],"category_scores_gemma":[0.01280121,0.000480178,0.0006638637,0.002979983,0.002284493,0.002037551,0.004777305,0.005727525,0.01617773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05234832,"about_ca_system_score_gemma":0.1815222,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8262184,"about_ca_topic_score_gemma":0.9285632,"domain_scores_codex":[0.9930693,0.0003853964,0.0001375661,0.0004512381,0.00477883,0.001177695],"domain_scores_gemma":[0.9682968,0.0009436572,0.0006449253,0.0005892043,0.01546278,0.01406261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.000009110458,0.000006280502,0.0007536262,0.00003261352,0.000002157009,0.00002716946,0.00004518875,0.00003235657,0.00006176971,0.001465729,0.9814004,0.01616368],"study_design_scores_gemma":[0.00002005119,0.00001710636,0.004871057,0.000219308,0.000007204473,0.00008685229,0.0002161892,0.00008923566,0.0001581142,0.0006405684,0.9936521,0.00002221982],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.004787305,0.016069,0.003949924,0.531521,0.03435312,0.001033485,0.02840215,0.002676156,0.3772079],"genre_scores_gemma":[0.06870914,0.03925754,0.02541989,0.1737145,0.01631559,0.0008583123,0.04806206,0.002293754,0.6253691],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1737816,"threshold_uncertainty_score":0.3798155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1375203965928787,"score_gpt":0.4322523954130915,"score_spread":0.2947319988202128,"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."}}