{"id":"W3128452488","doi":"10.1177/2053951720978991","title":"The cancer multiple: Producing and translating genomic big data into oncology care","year":2021,"lang":"en","type":"article","venue":"Big Data & Society","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Simon Fraser University; Genome Canada","keywords":"Big data; CONTEST; Personalized medicine; Data science; Computer science; Bioinformatics; Biology; Political science","routes":{"ca_aff":true,"ca_fund":true,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.06498488,0.000618734,0.0006554492,0.0027597,0.02615099,0.01747429,0.002483146,0.00415536,0.003549125],"category_scores_gemma":[0.08897694,0.0008579264,0.0007221396,0.00292955,0.06529128,0.0157016,0.02129316,0.01239127,0.0004088277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02538882,"about_ca_system_score_gemma":0.03666653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0958019,"about_ca_topic_score_gemma":0.09436128,"domain_scores_codex":[0.8806787,0.1046484,0.001641745,0.002471494,0.006515739,0.004043994],"domain_scores_gemma":[0.913564,0.07195732,0.003051145,0.003220549,0.00394806,0.004258957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003048893,0.00001568034,0.002699762,0.0001031537,0.00001624587,0.0004123286,0.9053928,0.0001574829,0.0002744286,0.07707474,0.004279428,0.009543515],"study_design_scores_gemma":[0.0000279071,0.00005002401,0.001397373,0.0005800644,0.0000238573,0.0003118957,0.8004909,0.0005585417,0.0003430624,0.05371911,0.142426,0.00007132018],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2812177,0.009736255,0.05218061,0.5357025,0.001452252,0.0004946452,0.0002612814,0.0002034568,0.1187512],"genre_scores_gemma":[0.968601,0.002723299,0.008774191,0.01594982,0.0002286576,0.0002031248,0.00005353255,0.0001551852,0.003311178],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.973849,"threshold_uncertainty_score":0.343677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08270260390087346,"score_gpt":0.3221955651368332,"score_spread":0.2394929612359597,"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."}}