{"id":"W2920887687","doi":"10.1093/aje/kwy280","title":"A Future for Observational Epidemiology: Clarity, Credibility, Transparency","year":2018,"lang":"en","type":"article","venue":"American Journal of Epidemiology","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Observational study; Epidemiology; CLARITY; Credibility; Transparency (behavior); Psychological intervention; Medicine; Causal inference; Population; Environmental health; Computer science; Pathology; Psychiatry; Biology","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":["metaresearch"],"category_scores_codex":[0.3120728,0.001207775,0.003529561,0.005170502,0.005564268,0.0204228,0.004487843,0.01541683,0.007538385],"category_scores_gemma":[0.5165401,0.001467251,0.002893201,0.00292066,0.04342613,0.05215034,0.01166059,0.03428441,0.001730895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007416253,"about_ca_system_score_gemma":0.01645402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003181899,"about_ca_topic_score_gemma":0.002078224,"domain_scores_codex":[0.7996644,0.1660028,0.007364969,0.006615946,0.01874143,0.001610415],"domain_scores_gemma":[0.2943023,0.6038907,0.01512753,0.04600622,0.03451206,0.006161182],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001006434,0.00004535499,0.0006553103,0.0005816916,0.00007441018,0.0001028027,0.001555584,0.0009208836,0.0001379209,0.9324864,0.0208449,0.04249422],"study_design_scores_gemma":[0.00003239692,0.00002040462,0.0002373013,0.0007425206,0.0000239792,0.00007858684,0.0003194883,0.0009871325,0.00007094755,0.9629673,0.03448128,0.00003854512],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001525376,0.04345981,0.1297464,0.8073306,0.008063375,0.0001221126,0.0001618159,0.0001951484,0.009395376],"genre_scores_gemma":[0.2624809,0.06561676,0.4431236,0.1717531,0.0474084,0.001745727,0.0003845055,0.0004333791,0.007053615],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.6879272,"threshold_uncertainty_score":0.8483368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4576903200979097,"score_gpt":0.5216762008091765,"score_spread":0.06398588071126687,"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."}}