{"id":"W4322012252","doi":"10.1016/j.esmoop.2023.100808","title":"78P Electronic tool for high grade adverse event (AE) reporting in gynecology (gyne) clinical trials (ClinT) at Princess Margaret Cancer Centre (PM)","year":2023,"lang":"en","type":"article","venue":"ESMO Open","topic":"Biomedical Ethics and Regulation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network","funders":"","keywords":"Medicine; Odds ratio; Adverse effect; Internal medicine; Odds; Gynecology; Logistic regression","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":[0.02678318,0.001199222,0.002564597,0.01238125,0.0005123377,0.003069675,0.001436396,0.001302701,0.129987],"category_scores_gemma":[0.1156908,0.0007618814,0.001622241,0.01141006,0.0004700701,0.002444203,0.003938055,0.001551848,0.02549013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001483956,"about_ca_system_score_gemma":0.004122576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007550436,"about_ca_topic_score_gemma":0.001619825,"domain_scores_codex":[0.9720196,0.0143986,0.008635826,0.001200303,0.003107826,0.0006378395],"domain_scores_gemma":[0.7786455,0.1206483,0.07263191,0.01000313,0.01370783,0.00436335],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004474299,0.0003124844,0.03542224,0.009947492,0.0007206493,0.0002819769,0.0003172721,0.001064761,0.0005843837,0.004743384,0.742955,0.1991761],"study_design_scores_gemma":[0.007074421,0.001414792,0.1461818,0.004874965,0.0009139814,0.001725573,0.0003973561,0.008315268,0.002739162,0.01355733,0.8124529,0.0003523978],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.02322974,0.0044202,0.04046234,0.006387549,0.000636203,0.02358773,0.8222762,0.0244039,0.05459625],"genre_scores_gemma":[0.198669,0.00569599,0.1601314,0.007492103,0.001642443,0.1436844,0.4372949,0.005830722,0.03955913],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.9732168,"threshold_uncertainty_score":0.4348497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.180920984992284,"score_gpt":0.4988707980387324,"score_spread":0.3179498130464483,"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."}}