{"id":"W2794363479","doi":"10.1093/milmed/usx193","title":"Letter in Response to Kim M, Torrie I, Poisson R, Withers N, Bjarnason S, DaLuz LT, Pannell D, Beckett A, Tien HC. The Value of Live Tissue Training for Combat Casualty Care: A Survey of Canadian Combat Medics with Battlefield Experience in Afghanistan. Mil Med. 2017 Sep;182(9):e1834–e1840","year":2018,"lang":"en","type":"letter","venue":"Military Medicine","topic":"Trauma, Hemostasis, Coagulopathy, Resuscitation","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Withers; Medicine; Value (mathematics); Gerontology; Mathematics; Internal medicine; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004715614,0.0009600631,0.002310509,0.001849977,0.0001708622,0.00001068348,0.0009728945,0.001004333,0.0001625038],"category_scores_gemma":[0.005166105,0.0007080066,0.0001286466,0.001828434,0.001542428,0.0001545962,0.00009554421,0.001755324,0.000007095022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001149492,"about_ca_system_score_gemma":0.001994973,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.499877,"about_ca_topic_score_gemma":0.7362252,"domain_scores_codex":[0.9921429,0.001528734,0.001837968,0.001291119,0.001831302,0.00136796],"domain_scores_gemma":[0.9922433,0.003753848,0.0005513487,0.001716083,0.001138747,0.0005966753],"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":[0.01036721,0.0001099389,0.01491974,0.001353476,0.0002157966,0.001426405,0.2169323,0.00006025391,0.001471357,0.000005639237,0.7507198,0.002418103],"study_design_scores_gemma":[0.01746677,0.01894963,0.3516816,0.014409,0.0008314864,0.0003415323,0.07716175,0.0003322233,0.00180891,0.0000393221,0.5150536,0.001924279],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7380157,0.006257423,0.0001114733,0.2482169,0.001275758,0.004348473,0.001450948,0.00003648771,0.0002868149],"genre_scores_gemma":[0.8536744,0.0002794542,0.001481343,0.1383898,0.001618876,0.0005222372,0.002874929,0.0002720027,0.0008869455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3367618,"threshold_uncertainty_score":0.9995371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09352818487451814,"score_gpt":0.3347742906073105,"score_spread":0.2412461057327924,"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."}}