{"id":"W2793808829","doi":"10.1097/ede.0000000000000820","title":"Synthesizing Risk from Summary Evidence Across Multiple Risk Factors","year":2018,"lang":"en","type":"article","venue":"Epidemiology","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital","funders":"","keywords":"Medicine; Population; Risk assessment; Index (typography); Statistics; Actuarial science; Environmental health; Computer science; Mathematics; Economics","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":[0.00134955,0.0001831721,0.0006797459,0.00002674367,0.0004242596,0.000003826321,0.0001206458,0.0001817563,0.00026265],"category_scores_gemma":[0.03962655,0.0001349886,0.0001872887,0.00008965159,0.000461066,0.0000660346,0.0001479775,0.0003304676,0.0002875679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006972183,"about_ca_system_score_gemma":0.00002111765,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01160427,"about_ca_topic_score_gemma":0.000704109,"domain_scores_codex":[0.9979415,0.0005284795,0.0004555982,0.0004625525,0.00009858786,0.0005132661],"domain_scores_gemma":[0.9809712,0.01814111,0.0002611301,0.0003465722,0.0001099546,0.0001700213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002829343,0.00005199283,0.967948,0.00001106584,0.0001391268,0.000007517025,0.0002044455,0.000002892846,0.0002264555,0.00004418752,0.02879946,0.00228192],"study_design_scores_gemma":[0.0005221501,0.0003340836,0.9538176,0.0001934668,0.00009621797,0.000004364258,0.0003906481,0.0003631702,0.0004270252,0.003897981,0.03981674,0.0001365711],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9873514,0.00777449,0.001155817,0.002178468,0.0005483957,0.000186864,0.0003402884,0.00008828262,0.0003759975],"genre_scores_gemma":[0.9856928,0.005822515,0.005194599,0.001495653,0.001594745,0.00001924804,0.00004428673,0.00001815799,0.0001180049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.038277,"threshold_uncertainty_score":0.9949775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1352627547857589,"score_gpt":0.3903758412595615,"score_spread":0.2551130864738027,"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."}}