{"id":"W4412488824","doi":"10.1002/wjs.70009","title":"Establishing an Essential Dataset for Trauma Registry in LMICs: Insights From a Delphi Survey","year":2025,"lang":"en","type":"article","venue":"World Journal of Surgery","topic":"Trauma and Emergency Care Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Medicine; Delphi method; Medical emergency; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000925071,0.0001528905,0.0006655368,0.0007197238,0.00008229819,0.00004252268,0.0001466631,0.00006289457,0.00004293357],"category_scores_gemma":[0.0009811901,0.0001301905,0.0001904024,0.0005819598,0.0000576319,0.0003872376,0.00003259776,0.0003265397,9.394655e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007417236,"about_ca_system_score_gemma":0.0002902611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001392954,"about_ca_topic_score_gemma":0.01481636,"domain_scores_codex":[0.998331,0.0001281272,0.0008625517,0.0002039764,0.0002426176,0.0002317255],"domain_scores_gemma":[0.9978188,0.001266693,0.0002786387,0.0002658341,0.0002528111,0.0001172193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003118291,0.0005603703,0.519725,0.0002130448,0.000564943,0.0005821386,0.0008686489,0.00003519763,0.001369611,0.00007378371,0.427956,0.04493305],"study_design_scores_gemma":[0.001529512,0.00004924769,0.9379035,0.001117782,0.0001905349,0.00002307083,0.0009906205,0.00004421907,0.0007008423,0.0007100307,0.05655298,0.0001876185],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903272,0.005093532,0.0003675018,0.0008565366,0.002171744,0.0001149489,0.0007207909,0.000009336035,0.0003383869],"genre_scores_gemma":[0.997081,0.0004400025,0.000431484,0.000335309,0.0005758416,0.000004591821,0.001000233,0.00001529325,0.0001162215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4181786,"threshold_uncertainty_score":0.8267875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07362380429098472,"score_gpt":0.3468517696088009,"score_spread":0.2732279653178161,"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."}}