{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002714072,0.0001383769,0.0001397334,0.000004194131,0.000373034,0.00009094373,0.000782322,0.0001336143,0.000001963498],"category_scores_gemma":[0.0003008892,0.000119103,0.00004369436,0.00007302649,0.0001332794,0.000006227534,0.002050088,0.0001391439,0.000001059215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005585371,"about_ca_system_score_gemma":0.0009015132,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008009605,"about_ca_topic_score_gemma":0.02771241,"domain_scores_codex":[0.9985799,0.0000473341,0.000201637,0.0008444583,0.00008322963,0.0002434745],"domain_scores_gemma":[0.997676,0.00007709799,0.0000791444,0.002004412,0.00009334342,0.0000700491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002255254,0.0000252904,0.00380606,0.00007839877,0.0001590069,0.000004133599,0.003761317,0.0000362028,0.3583074,0.000004224396,0.02792903,0.6058664],"study_design_scores_gemma":[0.0007286284,0.00004393196,0.003012259,0.00002131663,0.00009044365,0.00001086289,0.005866021,0.001018753,0.01339035,0.000018752,0.9755573,0.0002414278],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.755484,0.2318669,0.00194068,0.003777889,0.002038408,0.0003929881,0.004317067,0.00001867363,0.0001633606],"genre_scores_gemma":[0.9305546,0.0528654,0.004539579,0.001007132,0.00278604,0.00002625588,0.008124609,0.00003754236,0.00005879584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9476282,"threshold_uncertainty_score":0.9900293,"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."}}