{"id":"W2285427682","doi":"10.1111/cas.12857","title":"Report on the use of non‐clinical studies in the regulatory evaluation of oncology drugs","year":2016,"lang":"en","type":"review","venue":"Cancer Science","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation Cluster (Canada)","funders":"","keywords":"Cancer; Medicine; Clinical Oncology; Tumor microenvironment; Carcinogenesis; Oncology; Drug development; Bioinformatics; Metastasis; Internal medicine; Biology; Pharmacology; Drug","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03518587,0.0001931085,0.0009197811,0.0002655601,0.0001059182,0.00004321149,0.003008043,0.00008821089,0.000005087863],"category_scores_gemma":[0.005370294,0.00008648486,0.0002438873,0.001920708,0.002176949,0.0004356454,0.0006198349,0.000277952,0.000004093516],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006343711,"about_ca_system_score_gemma":0.008664833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002063928,"about_ca_topic_score_gemma":0.00001005499,"domain_scores_codex":[0.9928609,0.002818905,0.001264354,0.0007449301,0.002079346,0.0002315373],"domain_scores_gemma":[0.9853694,0.01040308,0.001554179,0.001649104,0.0009870009,0.00003717387],"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":[0.000001536553,0.0000383819,0.000009788612,0.0002160215,0.00002300917,0.000004013884,0.0005627044,0.000737162,4.680196e-7,0.006862934,0.0005220384,0.9910219],"study_design_scores_gemma":[0.0004430985,0.0003367453,0.003780603,0.02013444,0.0003355615,0.00009099483,0.0001354205,0.02512093,0.00003551921,0.00940241,0.9396873,0.0004969618],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001707135,0.9874901,0.004866413,0.00098146,0.002941761,0.001404423,0.000009908593,0.00001048959,0.0005883693],"genre_scores_gemma":[0.001623211,0.9937234,0.003878326,0.0002602424,0.0001472486,0.0003076019,6.465308e-7,0.000008084246,0.00005125068],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.990525,"threshold_uncertainty_score":0.9969551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6354481798060508,"score_gpt":0.61335080976673,"score_spread":0.02209737003932088,"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."}}