{"id":"W4385269880","doi":"10.1016/j.burns.2023.07.003","title":"Burn data management and usage across Canada","year":2023,"lang":"en","type":"article","venue":"Burns","topic":"Burn Injury Management and Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada Research Chairs; SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Benchmarking; Respondent; Medicine; Data collection; Descriptive statistics; Data quality; Burn center; Thematic analysis; Burn injury; Medical emergency; Qualitative property; Family medicine; Operations management; Qualitative research; Poison control; Statistics; Surgery","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002202654,0.00009607507,0.0001469614,0.00003268038,0.00008750104,0.00003360083,0.0001962052,0.00002279911,0.0001205607],"category_scores_gemma":[0.00002093057,0.00008062249,0.00001560987,0.0002420598,0.00003697232,0.00007328391,0.000632512,0.00007314212,0.00006871491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003252505,"about_ca_system_score_gemma":0.00002232095,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0339908,"about_ca_topic_score_gemma":0.09459466,"domain_scores_codex":[0.99906,0.000008531721,0.0001306002,0.0002631845,0.0002457705,0.000291911],"domain_scores_gemma":[0.9992219,0.00002582164,0.00002508689,0.0006185113,0.00001180914,0.00009688351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005379611,0.00003465531,0.1590475,0.000484854,0.0003288116,0.001897161,0.0002672594,0.000003359568,0.0000410034,0.001841999,0.7727655,0.06323407],"study_design_scores_gemma":[0.0006322583,0.00001818397,0.3373699,0.00003327939,0.00005784049,0.000008074498,0.0007137161,0.0003386535,0.00001898086,0.00006211027,0.6606533,0.00009367875],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9566537,0.0004268375,0.0001247508,0.01133576,0.000740837,0.0006120143,0.0001608791,0.0002712333,0.02967402],"genre_scores_gemma":[0.9049341,0.0004703636,0.0002695824,0.002020837,0.000163108,0.00001026645,0.0003237246,0.00002202631,0.09178601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1783224,"threshold_uncertainty_score":0.9724419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05407518746578072,"score_gpt":0.3291543310992502,"score_spread":0.2750791436334695,"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."}}