{"id":"W3163142507","doi":"10.1111/hex.13244","title":"Processes for evidence summarization for patient decision aids: A Delphi consensus study","year":2021,"lang":"en","type":"article","venue":"Health Expectations","topic":"Delphi Technique in Research","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Automatic summarization; Delphi method; Decision aids; Delphi; Computer science; Process (computing); Stakeholder; Evidence-based medicine; Critical appraisal; Knowledge management; MEDLINE; Psychology; Medical education; Medicine; Information retrieval; Alternative medicine; Artificial intelligence; Public relations","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","sts"],"consensus_categories":[],"category_scores_codex":[0.0006717946,0.00008835939,0.000171177,0.0001472526,0.001473162,0.000123772,0.0001705592,0.0000602388,0.00002000499],"category_scores_gemma":[0.02460672,0.00009480471,0.00005092962,0.001042346,0.00008505225,0.0001579302,0.00003891599,0.00007355573,0.000004972548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000283977,"about_ca_system_score_gemma":0.003981523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006015165,"about_ca_topic_score_gemma":0.01073332,"domain_scores_codex":[0.9979351,0.0003416553,0.0004504464,0.0003627859,0.0005017897,0.0004082674],"domain_scores_gemma":[0.9908621,0.006299306,0.0001687134,0.0002187163,0.002278652,0.0001724746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005742504,0.003093177,0.01398019,0.001121784,0.00007953616,0.00001350395,0.5689701,0.0002567903,0.0002935312,0.02760108,0.09466791,0.2893481],"study_design_scores_gemma":[0.001349704,0.00291524,0.001194724,0.0006738274,0.00003495978,0.000003449007,0.91286,0.0005074731,0.0006403283,0.02492053,0.05450205,0.0003977068],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.292473,0.01664019,0.5822642,0.07074906,0.001507562,0.03400814,0.0004415878,0.001024294,0.0008920052],"genre_scores_gemma":[0.8901069,0.0002573133,0.1045614,0.000305862,0.0001120073,0.004424681,0.00003515502,0.00002125587,0.0001754616],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.597634,"threshold_uncertainty_score":0.9998268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2740373297419293,"score_gpt":0.5462272779974153,"score_spread":0.272189948255486,"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."}}