{"id":"W2740384655","doi":"10.1158/1538-7445.am2017-378","title":"Abstract 378: The Cancer Genome Collaboratory","year":2017,"lang":"en","type":"article","venue":"Cancer Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; Concordia University; McGill University; BC Cancer Agency; Ontario Institute for Cancer Research","funders":"","keywords":"Collaboratory; Cloud computing; Interoperability; Computer science; Genome; Metadata; Software; Genomics; Computational biology; Data mining; Data science; Biology; World Wide Web; Genetics; Gene; Operating system","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":[0.01489767,0.001325432,0.001316808,0.003231267,0.003495359,0.006212228,0.004320596,0.00201113,0.1163355],"category_scores_gemma":[0.01830692,0.0007031441,0.0009887828,0.00509386,0.0009789678,0.0029268,0.007802473,0.003782871,0.05778017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006112686,"about_ca_system_score_gemma":0.01783843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03967268,"about_ca_topic_score_gemma":0.04400646,"domain_scores_codex":[0.9904384,0.002255946,0.0004573197,0.002288327,0.003482277,0.001077807],"domain_scores_gemma":[0.9629688,0.002590273,0.0009860337,0.007101501,0.01379835,0.01255499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002306573,0.00006321156,0.002528693,0.00007811333,0.00002432128,0.0001119148,0.00008315098,0.0002312361,0.0007296955,0.002498863,0.9702359,0.02318432],"study_design_scores_gemma":[0.0002470007,0.00008019298,0.003654658,0.0001009448,0.00002318484,0.0001565199,0.0001274982,0.001019297,0.001006664,0.001797886,0.9917494,0.00003682468],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.01874421,0.008492325,0.02534216,0.1070032,0.01535996,0.002250767,0.4365104,0.03525591,0.3510411],"genre_scores_gemma":[0.08927481,0.0030279,0.0548196,0.01917331,0.004879848,0.002372576,0.6614428,0.01115091,0.1538582],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1163355,"threshold_uncertainty_score":0.389181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06700933428036979,"score_gpt":0.4164437830424406,"score_spread":0.3494344487620709,"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."}}