{"id":"W3184405065","doi":"10.1177/0272989x211026292","title":"Simulating Study Data to Support Expected Value of Sample Information Calculations: A Tutorial","year":2021,"lang":"en","type":"article","venue":"Medical Decision Making","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; SickKids Foundation; Hospital for Sick Children; Public Health Ontario; University of Toronto","funders":"Medical Research Council; Norges Forskningsråd; University of Bristol; Department of Health and Social Care; Strong; Canadian Institutes of Health Research; National Institute for Health and Care Research; University Hospitals Bristol NHS Foundation Trust","keywords":"Bridging (networking); Missing data; Probabilistic logic; Sample (material); Key (lock); Value (mathematics); Outcome (game theory); Sample size determination","routes":{"ca_aff":true,"ca_fund":true,"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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01762135,0.0001442054,0.000802512,0.0003663411,0.0001797091,0.0001115063,0.0006023715,0.0001532311,0.00261667],"category_scores_gemma":[0.140453,0.0001742688,0.00007271553,0.0006001018,0.00002624859,0.0008994031,0.0005720633,0.0001879059,0.0006263959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000233001,"about_ca_system_score_gemma":0.0004659017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003837762,"about_ca_topic_score_gemma":0.000214909,"domain_scores_codex":[0.9930115,0.0003463787,0.005245249,0.0005090224,0.0005921812,0.0002956318],"domain_scores_gemma":[0.9905333,0.006295968,0.001423415,0.00124486,0.000235463,0.0002670272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003200852,0.001941599,0.4999926,0.000703865,0.0004868272,0.00005705221,0.03750965,0.03500961,0.000009010399,0.1429236,0.09696988,0.1840762],"study_design_scores_gemma":[0.005094733,0.0005256022,0.1398207,0.0009205295,0.00003856393,0.00002058145,0.0106238,0.633539,0.000006773155,0.02466247,0.1838759,0.0008713286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4907034,0.00009898045,0.5021594,0.002994309,0.001977119,0.0008283654,0.0005183945,0.00005586727,0.0006641729],"genre_scores_gemma":[0.943758,0.000004863338,0.05055456,0.004818909,0.0005311446,0.00003264772,0.0002657561,0.00001716283,0.00001697626],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5985294,"threshold_uncertainty_score":0.9982951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4848813593112004,"score_gpt":0.5247604619037006,"score_spread":0.03987910259250022,"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."}}