{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01328793,0.0002816209,0.001867929,0.0001775444,0.0001288629,0.000003080328,0.0006282415,0.000237311,0.000175094],"category_scores_gemma":[0.05199665,0.0002170013,0.0004446972,0.000282936,0.001825548,0.0002203438,0.0000591423,0.0006292797,0.000005089624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001394249,"about_ca_system_score_gemma":0.0002096846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003436393,"about_ca_topic_score_gemma":0.00005559141,"domain_scores_codex":[0.9945233,0.001900497,0.002385811,0.0003807321,0.0001305601,0.0006790463],"domain_scores_gemma":[0.9657648,0.02965064,0.002786489,0.0004958791,0.001046303,0.0002559381],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000531549,0.0001850328,0.1475121,0.00005613771,0.0002060063,0.000004808704,0.0003077882,0.00001434242,0.0002672195,0.7674565,0.04611556,0.03734288],"study_design_scores_gemma":[0.0003243974,0.003498533,0.02304215,0.00005508409,0.00008015497,0.0001660849,0.0001763236,0.0002779449,0.00009096762,0.9477518,0.02433563,0.0002009778],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09634319,0.0003547347,0.8816432,0.02031374,0.0006206014,0.0003091829,0.00005036313,0.00008755892,0.000277381],"genre_scores_gemma":[0.2321302,0.00020904,0.7599452,0.005136382,0.002452828,0.00004959051,0.00001062044,0.00003200284,0.00003417668],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1802952,"threshold_uncertainty_score":0.9559888,"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."}}