{"id":"W3082682241","doi":"10.1158/1538-7445.am2020-1680","title":"Abstract 1680: Assessment of statistical power in one mouse per treatment design for preclinical anticancer agent PDX large scale drug screens","year":2020,"lang":"en","type":"article","venue":"Cancer Research","topic":"Cancer Cells and Metastasis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network","funders":"","keywords":"Medicine; Cancer; In vivo; False positive paradox; Lung cancer; Drug; Oncology; Pharmacology; Internal medicine; Biology; Computer science; Machine learning","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.06320926,0.001523098,0.002332213,0.001708833,0.0007938985,0.001265134,0.001540696,0.002549408,0.009674268],"category_scores_gemma":[0.06262755,0.0009390572,0.002487462,0.001316738,0.001962679,0.001246481,0.001434734,0.003656009,0.000983679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001183101,"about_ca_system_score_gemma":0.001176442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003127616,"about_ca_topic_score_gemma":0.0002709758,"domain_scores_codex":[0.93657,0.04485301,0.003852269,0.004832497,0.008493857,0.001398396],"domain_scores_gemma":[0.8875072,0.0747503,0.01414402,0.01292452,0.009162334,0.001511663],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.1892432,0.01780202,0.03146238,0.004693762,0.003872134,0.0007340837,0.002318456,0.0331523,0.5251594,0.01131183,0.009786639,0.1704637],"study_design_scores_gemma":[0.01743345,0.3309882,0.08872407,0.0004433581,0.002978244,0.0008156424,0.0003952171,0.1136079,0.4042838,0.007372255,0.0324715,0.0004863683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5809378,0.001073035,0.3689352,0.0005475457,0.0008039422,0.03338325,0.003616611,0.001911727,0.008790942],"genre_scores_gemma":[0.6185531,0.0002340518,0.2882439,0.000568152,0.000149027,0.08649665,0.001321903,0.0006179867,0.003815229],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9367908,"threshold_uncertainty_score":0.3342865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3029285319059805,"score_gpt":0.5175469428655607,"score_spread":0.2146184109595802,"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."}}