{"id":"W2997823527","doi":"10.1002/cam4.2812","title":"Developing a cancer‐specific trigger tool to identify treatment‐related adverse events using administrative data","year":2020,"lang":"en","type":"article","venue":"Cancer Medicine","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Tellabs (Canada)","funders":"National Cancer Institute; AARP Foundation","keywords":"Medicine; Prostate cancer; Adverse effect; Cancer; Lung cancer; Internal medicine; Colorectal cancer; Disease; Metastatic breast cancer; Breast cancer; Oncology; Intensive care 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":[0.01360423,0.0008146235,0.0009205916,0.009160733,0.0005678429,0.002556375,0.001183703,0.0008098948,0.001886813],"category_scores_gemma":[0.05370492,0.0003648086,0.001877202,0.005781247,0.000216537,0.001749241,0.002049441,0.000913801,0.0005967563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001143682,"about_ca_system_score_gemma":0.003181265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005567018,"about_ca_topic_score_gemma":0.007108777,"domain_scores_codex":[0.9912626,0.00310716,0.002576852,0.0009437935,0.001661096,0.0004484798],"domain_scores_gemma":[0.9508416,0.02315035,0.01596134,0.002600495,0.005963547,0.001482591],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001253736,0.0002601523,0.9383194,0.0003309514,0.0004120682,0.00008686513,0.0003050703,0.001866944,0.0002498071,0.0005385851,0.005232449,0.05227248],"study_design_scores_gemma":[0.0002085669,0.0007627488,0.9088166,0.0007356567,0.0005576225,0.0004862723,0.00166987,0.06719624,0.002496836,0.003710812,0.0132211,0.0001377111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8345702,0.001543932,0.08933716,0.003103799,0.0002248587,0.006110945,0.0532047,0.00287675,0.009027719],"genre_scores_gemma":[0.8696862,0.0004996586,0.1031706,0.0005607883,0.0001094755,0.002875241,0.02261069,0.00006030026,0.0004269594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01360423,"threshold_uncertainty_score":0.07194698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5369607288966759,"score_gpt":0.5149304900090929,"score_spread":0.02203023888758304,"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."}}