{"id":"W2962568023","doi":"10.1016/j.annepidem.2019.07.010","title":"Response to Acquavella J, conflict of interest: a hazard for epidemiology","year":2019,"lang":"en","type":"letter","venue":"Annals of Epidemiology","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Confounding; Observational error; Statistics; Medicine; Sample size determination; Hazard ratio; Standard error; Observational study; Random error; Sample (material); Errors-in-variables models; Citation; Econometrics; Confidence interval; Computer science; Mathematics","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","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.01184553,0.001091154,0.00303128,0.001844601,0.003693021,0.006043657,0.001986389,0.0515129,0.007624825],"category_scores_gemma":[0.1278335,0.001220437,0.001533325,0.002072301,0.003275774,0.003485766,0.002407512,0.04825484,0.007098233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005580359,"about_ca_system_score_gemma":0.005830777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006332098,"about_ca_topic_score_gemma":0.01016999,"domain_scores_codex":[0.9918834,0.002689518,0.001422119,0.001125073,0.002352804,0.0005271691],"domain_scores_gemma":[0.9363858,0.0403599,0.00489551,0.001750022,0.0113959,0.005212973],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006578497,0.0000108928,0.0005075604,0.0001191319,0.00003535402,0.0003666605,0.0000614238,0.00002830478,0.00005767135,0.0007085824,0.993842,0.004196793],"study_design_scores_gemma":[0.0007393056,0.0001173364,0.003267593,0.001824177,0.0002976478,0.002235873,0.0006589303,0.001191001,0.0004080397,0.01204074,0.9770417,0.0001777718],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00008940093,0.0008708532,0.00008094197,0.9799325,0.01847013,0.00001029759,0.00008284628,0.00001590016,0.0004471571],"genre_scores_gemma":[0.001253935,0.0007396579,0.0002880599,0.94716,0.04890382,0.00004914438,0.00003936603,0.00002214855,0.001543863],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9881545,"threshold_uncertainty_score":0.06264591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9593542961996878,"score_gpt":0.6488817582065084,"score_spread":0.3104725379931794,"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."}}