{"id":"W4405218885","doi":"10.1093/heapol/czae119","title":"Implementation science research priorities for Universal Health Coverage: methodological lessons from the design and implementation of a multicountry modified Delphi study","year":2024,"lang":"en","type":"article","venue":"Health Policy and Planning","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research; Public Health Ontario; University of Toronto","funders":"Canadian Institutes of Health Research; University of Toronto; University of Melbourne","keywords":"Delphi; Delphi method; Implementation research; Developing country; Engineering management; Computer science; Universal design; Business; Process management; Management science; Engineering; Medicine; Economic growth; Nursing; Psychological intervention; Economics","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"],"consensus_categories":[],"category_scores_codex":[0.05923696,0.0001046357,0.0004681926,0.0004217042,0.00102586,0.0001721354,0.0001389198,0.000044102,0.00001244322],"category_scores_gemma":[0.001844691,0.0001008437,0.0000236303,0.0003435895,0.0001777437,0.0003523926,0.00006681478,0.0001832049,0.000002488756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005445109,"about_ca_system_score_gemma":0.001959373,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06235821,"about_ca_topic_score_gemma":0.0007430169,"domain_scores_codex":[0.9957823,0.001548571,0.001577501,0.0004578597,0.0001448035,0.000489014],"domain_scores_gemma":[0.9882045,0.01081867,0.0005861534,0.0001627462,0.00007494703,0.0001530159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001320509,0.00006250128,0.04719317,0.001565289,0.0001156928,0.000001174722,0.2768523,0.0008098658,0.00001417617,0.6425835,0.008599576,0.02207077],"study_design_scores_gemma":[0.003845475,0.002172649,0.4949046,0.0004563419,0.00001721458,0.000008074982,0.3389374,0.05384248,0.00001919202,0.0907959,0.01458369,0.0004169444],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7351944,0.007266078,0.1272438,0.1247424,0.0002549935,0.003949992,0.001279479,0.00003526681,0.00003352508],"genre_scores_gemma":[0.9865506,0.0005855205,0.008087177,0.00432598,0.0002701922,0.0001309232,0.00002800634,0.00001180488,0.0000097415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5517876,"threshold_uncertainty_score":0.9687135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8782040358380065,"score_gpt":0.6964622124922469,"score_spread":0.1817418233457596,"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."}}