{"id":"W3086884385","doi":"10.1002/pds.5079","title":"Improving transparency to build trust in <scp>real‐world</scp> secondary data studies for hypothesis testing—Why, what, and how: recommendations and a road map from the <scp>real‐world</scp> evidence transparency initiative","year":2020,"lang":"en","type":"article","venue":"Pharmacoepidemiology and Drug Safety","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Tellabs (Canada)","funders":"International Society for Pharmacoepidemiology; National Pharmaceutical Council","keywords":"Transparency (behavior); Comparative effectiveness research; Medicine; Outcomes research; Health care; Pharmacoeconomics; Real world evidence; Alternative medicine; Computer science; Political science","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","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01957864,0.0005233915,0.002017728,0.0003320351,0.0007544416,0.0001394531,0.0006944744,0.0001554805,0.00003899481],"category_scores_gemma":[0.05365248,0.0005292673,0.0001013108,0.0005193379,0.0003640884,0.002003495,0.0002973778,0.0006447595,0.00002573843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001990694,"about_ca_system_score_gemma":0.0002271403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005644213,"about_ca_topic_score_gemma":0.01267751,"domain_scores_codex":[0.9915555,0.002402973,0.003421786,0.001732,0.0000814166,0.0008063616],"domain_scores_gemma":[0.8676799,0.1289518,0.002007759,0.0006829702,0.0001252705,0.0005523321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001071182,0.0001333591,0.6341763,0.00201214,0.0008132819,0.000005949481,0.0601439,0.0002329367,0.00005260578,0.003863667,0.2495371,0.04892172],"study_design_scores_gemma":[0.005845038,0.0003882404,0.6003533,0.001907194,0.0004847549,0.00001054232,0.0445944,0.08533552,0.00003879879,0.03364609,0.2266816,0.000714529],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2496878,0.09445387,0.01561864,0.6209669,0.001515334,0.004577714,0.0122751,0.0001881742,0.0007164794],"genre_scores_gemma":[0.6814772,0.1309162,0.0491165,0.1341101,0.001870488,0.00121541,0.0006678629,0.0001615191,0.0004647497],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4868568,"threshold_uncertainty_score":0.9997159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6006322429748091,"score_gpt":0.4679675235392478,"score_spread":0.1326647194355613,"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."}}