{"id":"W4402446660","doi":"10.12688/f1000research.152514.1","title":"Methodology used to develop the minimum common data elements for surveillance and Reporting of Musculoskeletal Injuries in the MILitary (ROMMIL) statement","year":2024,"lang":"en","type":"preprint","venue":"F1000Research","topic":"Occupational Health and Performance","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Calgary; Department of National Defence","funders":"Uniformed Services University of the Health Sciences; U.S. Department of Defense","keywords":"Delphi method; Delphi; Likert scale; Subject-matter expert; Medicine; Scope (computer science); Medical education; Psychology; 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":[],"category_scores_codex":[0.2394305,0.002029379,0.001795178,0.01235793,0.003476083,0.004912946,0.003893635,0.00273065,0.01056074],"category_scores_gemma":[0.2258441,0.002110788,0.00347221,0.00666566,0.003314815,0.004102741,0.008115434,0.004057416,0.004410163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009057318,"about_ca_system_score_gemma":0.04829352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004346326,"about_ca_topic_score_gemma":0.005253289,"domain_scores_codex":[0.7690014,0.1561103,0.04181629,0.007671912,0.0220278,0.003372329],"domain_scores_gemma":[0.7314594,0.1058245,0.02537398,0.02342145,0.1100752,0.003845414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001094791,0.001563825,0.01913099,0.03272018,0.0003392006,0.00145611,0.1040715,0.004449993,0.01751419,0.04306036,0.04637286,0.7282259],"study_design_scores_gemma":[0.001257131,0.004644872,0.04511738,0.05283837,0.0005448962,0.001542564,0.108644,0.01027225,0.02849421,0.03304387,0.7128141,0.0007863311],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02645021,0.001008596,0.5276616,0.004678499,0.0006995425,0.416049,0.007653646,0.0007333554,0.0150656],"genre_scores_gemma":[0.01857117,0.0005171009,0.7153624,0.0008974198,0.00006089722,0.2607366,0.002264555,0.0001219387,0.001467819],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2394305,"threshold_uncertainty_score":0.9379176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6164590896042137,"score_gpt":0.648696315465842,"score_spread":0.03223722586162836,"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."}}