{"id":"W2487959321","doi":"10.1158/1538-7445.am2016-3632","title":"Abstract 3632: Adaptive operations and technology platform for nation-scale precision oncology","year":2016,"lang":"en","type":"article","venue":"Cancer Research","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Workflow; Scalability; Computer science; Precision medicine; Analytics; Data science; Scale (ratio); Predictive analytics; Big data; Data mining; Database; Medicine","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":[0.007408892,0.00102163,0.0006443202,0.001381493,0.000978841,0.00449683,0.002916416,0.001364662,0.01953851],"category_scores_gemma":[0.01031845,0.0006561483,0.0009798201,0.001181091,0.001418915,0.004985781,0.00701136,0.002722454,0.009464264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001637726,"about_ca_system_score_gemma":0.003800323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003688055,"about_ca_topic_score_gemma":0.001571604,"domain_scores_codex":[0.996605,0.0007568777,0.0002649955,0.0007106835,0.001237322,0.0004250212],"domain_scores_gemma":[0.992419,0.001284584,0.000462093,0.003075662,0.001568213,0.00119038],"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":[0.003278537,0.0009233517,0.02073511,0.0004866587,0.0002594073,0.001736618,0.002151723,0.1186481,0.05793452,0.1762181,0.1967634,0.4208646],"study_design_scores_gemma":[0.0005564348,0.001149444,0.005336165,0.0002454291,0.0001235328,0.0005283293,0.0005694507,0.4267091,0.02974978,0.1385638,0.3961812,0.0002873988],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04979235,0.0005628347,0.7880325,0.006184868,0.001142549,0.001529251,0.003615173,0.10744,0.04170045],"genre_scores_gemma":[0.4310141,0.0007262161,0.5217238,0.001709588,0.0004151977,0.001581565,0.01228859,0.005806516,0.02473434],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01953851,"threshold_uncertainty_score":0.06536287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07564222026282387,"score_gpt":0.40862806947769,"score_spread":0.3329858492148661,"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."}}