{"id":"W3160848562","doi":"10.1177/0272989x211073098","title":"Calculating Expected Value of Sample Information Adjusting for Imperfect Implementation","year":2022,"lang":"en","type":"article","venue":"Medical Decision Making","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","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":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Imperfect; Monte Carlo method; Matching (statistics); Sampling (signal processing); Sample (material); Moment (physics); Value of information; Expected value","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1269508,0.001508527,0.002374677,0.004006016,0.0007201329,0.002854816,0.00340461,0.002203827,0.005609792],"category_scores_gemma":[0.5232311,0.001069825,0.003391508,0.003240302,0.003287016,0.004826173,0.003922863,0.003442755,0.0006727657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003707447,"about_ca_system_score_gemma":0.00523032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002325813,"about_ca_topic_score_gemma":0.001614729,"domain_scores_codex":[0.8569875,0.1138771,0.007522325,0.00682501,0.01360362,0.001184401],"domain_scores_gemma":[0.4111277,0.5188653,0.02259127,0.03446462,0.01210085,0.000850242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0008456769,0.0002861644,0.05429088,0.002695976,0.00322157,0.0005134179,0.001586614,0.2029922,0.001407006,0.2538375,0.006932312,0.4713907],"study_design_scores_gemma":[0.000413016,0.001293169,0.02123024,0.002061876,0.001462397,0.0006068228,0.0004206867,0.5103043,0.007434724,0.4338538,0.02065701,0.0002618179],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009292254,0.0003865884,0.9866678,0.0004503514,0.0001051437,0.0005483468,0.0002377979,0.0002754592,0.002036261],"genre_scores_gemma":[0.2667371,0.0004601142,0.7282709,0.0004194909,0.0001154083,0.002575694,0.0004818639,0.0001918504,0.0007476095],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1269508,"threshold_uncertainty_score":0.671388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5071110705585236,"score_gpt":0.5631016622128868,"score_spread":0.05599059165436326,"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."}}