{"id":"W1703252754","doi":"10.7205/milmed-d-13-00446","title":"Classifying U.S. Army Military Occupational Specialties Using the Occupational Information Network","year":2014,"lang":"en","type":"article","venue":"Military Medicine","topic":"Occupational Health and Performance","field":"Health Professions","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Paul's Hospital","funders":"National Institute of Mental Health; University of California, San Diego; Veterans Affairs San Diego Healthcare System; U.S. Public Health Service; Uniformed Services University of the Health Sciences; U.S. Air Force","keywords":"Crew; Occupational safety and health; Active duty; Variance (accounting); Military personnel; Poison control; Psychological resilience; Psychology; Gerontology; Environmental health; Medicine; Business; Engineering; Political science; Social psychology; Aeronautics","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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002898446,0.0002594487,0.0003606266,0.0001751379,0.002546661,0.000002590009,0.0002899241,0.0002000355,0.001924926],"category_scores_gemma":[0.0008198734,0.0001731768,0.00006936608,0.0004753655,0.0003257156,0.0007102808,0.00009333591,0.0007949928,0.0003681277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002768625,"about_ca_system_score_gemma":0.0007489157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002374483,"about_ca_topic_score_gemma":0.0008977909,"domain_scores_codex":[0.9962412,0.0006707714,0.001253866,0.0002425275,0.0008667408,0.00072493],"domain_scores_gemma":[0.9969047,0.00172698,0.0002398424,0.0004282306,0.0004682806,0.0002319376],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001387663,0.00002908304,0.7417913,0.0007413373,0.00004244391,9.296185e-7,0.006162512,0.0130983,0.00001357952,0.008506076,0.2161507,0.01207611],"study_design_scores_gemma":[0.001009339,0.0001090483,0.6619627,0.0003344142,0.00002527583,0.000003734079,0.001138272,0.06988818,6.161843e-7,0.001395102,0.2639781,0.0001552179],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9222192,0.005565829,0.02342053,0.0162252,0.01000589,0.002271275,0.0001930788,0.0002724587,0.01982657],"genre_scores_gemma":[0.9452112,0.0004172469,0.004828278,0.02706194,0.02031489,0.0001540966,0.001536042,0.00002926158,0.000447025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07982865,"threshold_uncertainty_score":0.9989874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1082962298390041,"score_gpt":0.423232156184521,"score_spread":0.3149359263455169,"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."}}