{"id":"W4392302718","doi":"10.1016/j.semarthrit.2024.152423","title":"Defining domains: developing consensus-based definitions for foundational domains in OMERACT core outcome sets","year":2024,"lang":"en","type":"article","venue":"Seminars in Arthritis and Rheumatism","topic":"Delphi Technique in Research","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bruyère; Treasury Board of Canada Secretariat; University of Toronto; Institute for Work & Health; Toronto Western Hospital; Ottawa Hospital; Hospital for Sick Children; Institute of Infection and Immunity; University of Ottawa","funders":"Department of Health and Social Care; National Institute for Health and Care Research; Parker Institute for Cancer Immunotherapy; Leeds Biomedical Research Centre; Oak Foundation","keywords":"Medicine; Domain (mathematical analysis); Set (abstract data type); Core (optical fiber); Quality of life (healthcare); Medical education; Computer science; Nursing; Mathematics","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":[0.2396257,0.001069093,0.001816262,0.008491211,0.003428618,0.00816033,0.004186864,0.002243749,0.002567338],"category_scores_gemma":[0.359864,0.001060614,0.003767434,0.005563492,0.004933299,0.009671368,0.01489386,0.004722742,0.0006266064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01160004,"about_ca_system_score_gemma":0.02269495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004973394,"about_ca_topic_score_gemma":0.005946504,"domain_scores_codex":[0.8187855,0.1256846,0.02905132,0.005556007,0.01736664,0.003555937],"domain_scores_gemma":[0.6846051,0.2076886,0.0185257,0.02213277,0.06362277,0.003425058],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0007663186,0.0007494626,0.05116726,0.0075958,0.0007992163,0.0003320235,0.08679238,0.01912456,0.003375814,0.3250754,0.01447915,0.4897427],"study_design_scores_gemma":[0.0006999606,0.001193584,0.040427,0.01561746,0.001001959,0.0006257889,0.09904105,0.1441401,0.01189619,0.6131356,0.07166855,0.0005527557],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.077544,0.0004425713,0.8911396,0.003286992,0.0001602774,0.01203695,0.001513175,0.0005014311,0.01337503],"genre_scores_gemma":[0.1817276,0.0001275762,0.8040198,0.0003252735,0.00001409548,0.0110837,0.002078191,0.0001242547,0.0004994445],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7603743,"threshold_uncertainty_score":0.9376769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1554773912342132,"score_gpt":0.44790869079829,"score_spread":0.2924312995640768,"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."}}