{"id":"W2187313585","doi":"10.7205/milmed-d-12-00403","title":"Temporal Changes in Combat Casualties From Afghanistan by Nationality: 2006–2010","year":2013,"lang":"en","type":"article","venue":"Military Medicine","topic":"Disaster Response and Management","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Demography; Medicine; Population; Military personnel; Navy; Case fatality rate; Environmental health; Civilian population; Geography; Political science; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004948607,0.0003028934,0.0002285649,0.002056564,0.0006686714,0.0006858805,0.000478238,0.000467385,0.001978079],"category_scores_gemma":[0.001936705,0.0001902614,0.0002655798,0.002534596,0.0002270901,0.0007523434,0.0007194034,0.0006897351,0.0004953024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001596722,"about_ca_system_score_gemma":0.0009589887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1918699,"about_ca_topic_score_gemma":0.2915635,"domain_scores_codex":[0.9995241,0.00003988744,0.00005697131,0.0001085167,0.0001238947,0.0001466538],"domain_scores_gemma":[0.9984345,0.000102842,0.0007248198,0.00005521687,0.0005203081,0.000162251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001537588,0.00002790815,0.9907046,0.00004283289,0.00005172341,0.00007065931,0.0005263963,0.0001065913,0.0002525667,0.000045627,0.001345195,0.006672247],"study_design_scores_gemma":[0.000002026835,0.0000249647,0.9976764,0.00001631559,0.00001127629,0.0001301398,0.0006918582,0.000118236,0.00007595213,0.000008717281,0.001238785,0.000005347828],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890013,0.0008436281,0.0001699851,0.0003286509,0.00003576459,0.00001744687,0.007164943,0.00003151667,0.002406836],"genre_scores_gemma":[0.9899679,0.0006560924,0.0001598552,0.0001128303,0.00003709551,0.00002763272,0.008323495,0.00000903496,0.0007060643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1918699,"threshold_uncertainty_score":0.3815062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05950972980818344,"score_gpt":0.3796690102141628,"score_spread":0.3201592804059794,"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."}}