{"id":"W4286572051","doi":"10.1109/cogsima54611.2022.9830666","title":"Sensors-Enabled Human State Monitoring System for Tactical Settings","year":2022,"lang":"en","type":"article","venue":"","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thales (Canada)","funders":"","keywords":"Computer science; State (computer science); Comprehension; Order (exchange); Computer security; Business","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":[],"consensus_categories":[],"category_scores_codex":[0.000314821,0.0006070183,0.0005106099,0.0005910199,0.0002807198,0.0005627552,0.0006544951,0.0005308444,0.007083431],"category_scores_gemma":[0.0007414313,0.0002299071,0.0002070898,0.0003208276,0.0001332267,0.0006620463,0.0007728647,0.000521866,0.002963687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000242533,"about_ca_system_score_gemma":0.0003546675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001082314,"about_ca_topic_score_gemma":0.002237038,"domain_scores_codex":[0.9997843,0.00003319122,0.00001732424,0.00007056493,0.0000726388,0.00002215387],"domain_scores_gemma":[0.9997781,0.00004182279,0.00002522844,0.00003429739,0.00008123285,0.00003927186],"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":[0.003672351,0.0009867187,0.03316878,0.001233097,0.0003458356,0.001253581,0.001595314,0.007386176,0.1665652,0.005774499,0.1236856,0.6543329],"study_design_scores_gemma":[0.000599416,0.002664196,0.1613947,0.0005569679,0.0007101656,0.004651037,0.000983699,0.3856999,0.2025855,0.01500648,0.2247279,0.0004201998],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2944672,0.005416084,0.5216186,0.002910649,0.001816172,0.001347054,0.01813615,0.0950321,0.05925597],"genre_scores_gemma":[0.902936,0.0008720362,0.07350607,0.001301819,0.0002121977,0.000652405,0.004123486,0.0003471073,0.01604892],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007083431,"threshold_uncertainty_score":0.02369648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04539541613561656,"score_gpt":0.3458907629613872,"score_spread":0.3004953468257707,"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."}}