{"id":"W2614367461","doi":"10.1161/circoutcomes.6.suppl_1.a117","title":"Abstract 117: Application Of A Delphi Method To Develop A Patient Decision Aid For Implantable Cardioverter Defibrillator Candidates","year":2013,"lang":"en","type":"article","venue":"Circulation Cardiovascular Quality and Outcomes","topic":"Delphi Technique in Research","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Joseph’s Healthcare Hamilton; Hamilton Health Sciences; University of Ottawa; McMaster University; Population Health Research Institute","funders":"","keywords":"Delphi method; Likert scale; Delphi; Medicine; Nominal group; Health care; Psychology; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.09373558,0.001721462,0.001311106,0.005982264,0.005245135,0.004919244,0.00266803,0.001885127,0.01839683],"category_scores_gemma":[0.1265523,0.001306351,0.001584749,0.004071014,0.003354732,0.003330946,0.009987148,0.00242792,0.002056437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006885538,"about_ca_system_score_gemma":0.01413021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002524971,"about_ca_topic_score_gemma":0.003314232,"domain_scores_codex":[0.8436537,0.1354633,0.008193751,0.002629319,0.007949001,0.002110865],"domain_scores_gemma":[0.8994798,0.07209613,0.00357301,0.003218619,0.0199351,0.001697341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.001519348,0.001353774,0.006089528,0.008970438,0.0002360904,0.001767946,0.3807565,0.006548882,0.01706916,0.05121648,0.03416931,0.4903026],"study_design_scores_gemma":[0.001787394,0.00517774,0.01769917,0.008297755,0.0004141903,0.001477935,0.5350401,0.06527823,0.02403155,0.08666268,0.2534019,0.0007313042],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3064575,0.0005444507,0.4199591,0.006532016,0.000969114,0.2042047,0.00193673,0.000541288,0.05885502],"genre_scores_gemma":[0.254659,0.0004853063,0.6264665,0.001411091,0.0001421185,0.1083951,0.0007582604,0.0001426915,0.007539987],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09373558,"threshold_uncertainty_score":0.4957271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08985657308830913,"score_gpt":0.4318900455475964,"score_spread":0.3420334724592873,"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."}}