{"id":"W4252813111","doi":"10.23970/ahrqepcmethguide1","title":"Prioritization and Selection of Harms for Inclusion in Systematic Reviews","year":2017,"lang":"en","type":"report","venue":"","topic":"Delphi Technique in Research","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Vanderbilt University; Agency for Healthcare Research and Quality; Johns Hopkins University; U.S. Department of Health and Human Services","keywords":"Prioritization; Selection (genetic algorithm); Inclusion (mineral); Systematic review; Computer science; Actuarial science; Risk analysis (engineering); Data science; Management science; Psychology; Business; Political science; Economics; Artificial intelligence; MEDLINE; Social psychology; Law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.4216623,0.003998415,0.009151004,0.04183563,0.003798524,0.01148517,0.004226509,0.005803418,0.01272208],"category_scores_gemma":[0.6750734,0.003205425,0.01385038,0.02724292,0.00298264,0.009558965,0.01292666,0.005065598,0.002394498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008324505,"about_ca_system_score_gemma":0.04386022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003529771,"about_ca_topic_score_gemma":0.007051178,"domain_scores_codex":[0.3864215,0.3019758,0.195995,0.008686606,0.1019207,0.00500032],"domain_scores_gemma":[0.3269646,0.4419841,0.09325061,0.02861302,0.1035885,0.005599075],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"qualitative","study_design_scores_codex":[0.003167698,0.0002772362,0.02039302,0.4641578,0.00941648,0.0006065799,0.01118614,0.001303991,0.003066661,0.01426678,0.03534854,0.436809],"study_design_scores_gemma":[0.003854433,0.00135181,0.04639012,0.6502429,0.01943646,0.001367718,0.006478609,0.003853171,0.00897477,0.07655466,0.1808517,0.0006435703],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"methods","genre_scores_codex":[0.05462957,0.2460172,0.1275466,0.08222297,0.008190932,0.405081,0.03953543,0.001848005,0.03492829],"genre_scores_gemma":[0.1836755,0.08496307,0.3879825,0.009581685,0.003169808,0.3135918,0.01236029,0.0004204597,0.004254803],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5783377,"threshold_uncertainty_score":0.7131934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3323301262150563,"score_gpt":0.5570469542739996,"score_spread":0.2247168280589433,"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."}}