{"id":"W2766758581","doi":"10.1158/0008-5472.can-17-0598","title":"Developing Cancer Informatics Applications and Tools Using the NCI Genomic Data Commons API","year":2017,"lang":"en","type":"article","venue":"Cancer Research","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"National Cancer Institute; Research Committee, Aristotle University of Thessaloniki; National Institutes of Health; National Natural Science Foundation of China","keywords":"Informatics; Cancer; Commons; Computational biology; Data science; Computer science; Medicine; Biology; Political science; Internal medicine; Ecology","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":[0.007147156,0.001178711,0.0008836936,0.003503483,0.0008989512,0.003481755,0.003182098,0.0009066612,0.01390742],"category_scores_gemma":[0.01344922,0.0008896269,0.001410606,0.003256169,0.0008219234,0.002983382,0.007959619,0.001985711,0.009882257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00275149,"about_ca_system_score_gemma":0.00300573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01065086,"about_ca_topic_score_gemma":0.006492147,"domain_scores_codex":[0.9967835,0.0006308173,0.0003583907,0.0006958162,0.001253283,0.0002782456],"domain_scores_gemma":[0.994307,0.002226598,0.0002722542,0.001651699,0.001021516,0.0005209671],"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":[0.001363899,0.0007552257,0.02177232,0.001062211,0.0003220481,0.001486566,0.001755891,0.01021253,0.02856883,0.04616666,0.5785213,0.3080124],"study_design_scores_gemma":[0.0007929582,0.0001422449,0.01547263,0.0004203918,0.0001137478,0.0007694598,0.0004535438,0.1660471,0.05650959,0.04004712,0.7189245,0.0003067365],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.01860457,0.0004813682,0.3839138,0.002915638,0.0003171049,0.001783404,0.03205097,0.5280305,0.03190259],"genre_scores_gemma":[0.164383,0.0008517429,0.6122732,0.00287512,0.0002001525,0.003242324,0.141215,0.05596178,0.01899762],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01390742,"threshold_uncertainty_score":0.046525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2802541606702012,"score_gpt":0.4755309553354611,"score_spread":0.1952767946652599,"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."}}