{"id":"W4385781665","doi":"10.3171/2023.6.jns23702","title":"Core outcomes in nerve surgery: development of a core outcome set for ulnar neuropathy at the elbow","year":2023,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Orthopedic Surgery and Rehabilitation","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; McGill University","funders":"","keywords":"Medicine; Delphi method; Ulnar neuropathy; Outcome (game theory); Delphi; Elbow; Ulnar nerve; Population; Set (abstract data type); Core (optical fiber); Outcomes research; Physical therapy; Surgery; Physical medicine and rehabilitation; Alternative medicine; Artificial intelligence; Pathology; Computer science","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":[0.2068154,0.001533687,0.003809321,0.01290976,0.002065516,0.003871353,0.002781159,0.001684996,0.002302578],"category_scores_gemma":[0.2468308,0.0006636983,0.008221629,0.007157971,0.002075008,0.005088035,0.01020086,0.003298388,0.0005840882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006879557,"about_ca_system_score_gemma":0.02634407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002443004,"about_ca_topic_score_gemma":0.00379976,"domain_scores_codex":[0.8685045,0.06814382,0.03439327,0.00246106,0.02466227,0.001835055],"domain_scores_gemma":[0.7269006,0.1310143,0.04034823,0.01259493,0.08439381,0.004748196],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002607371,0.001639299,0.1446335,0.06571446,0.005031213,0.0002654682,0.008497146,0.01216366,0.002237118,0.03053,0.02095454,0.7057263],"study_design_scores_gemma":[0.00457765,0.01231294,0.513102,0.128498,0.01277767,0.001612402,0.02180921,0.05197235,0.0171541,0.1074072,0.1276636,0.001112787],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2727888,0.02270382,0.4906485,0.01771018,0.002133851,0.1351014,0.01812175,0.0009560805,0.0398357],"genre_scores_gemma":[0.2961441,0.003679899,0.5619974,0.001615346,0.0002710708,0.1244523,0.01093654,0.0001371839,0.0007661925],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7931846,"threshold_uncertainty_score":0.9781378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2066733420082894,"score_gpt":0.3730739191474989,"score_spread":0.1664005771392095,"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."}}