{"id":"W2096926032","doi":"10.1017/s1049023x1400140x","title":"Do You See What I See? Insights from Using Google Glass for Disaster Telemedicine Triage","year":2015,"lang":"en","type":"article","venue":"Prehospital and Disaster Medicine","topic":"Disaster Response and Management","field":"Health Professions","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. National Library of Medicine","keywords":"Triage; Telemedicine; Medical emergency; Intervention (counseling); Medicine; Mass-casualty incident; Emergency management; Emergency medicine; Nursing; Poison control; Health care; Human factors and ergonomics","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":[0.001880708,0.0004985824,0.0003650619,0.001312382,0.001249271,0.002873073,0.001014836,0.001195977,0.002622271],"category_scores_gemma":[0.01135094,0.0003035236,0.0005824593,0.0007460396,0.002071831,0.002791524,0.002317176,0.001109279,0.0006867537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008944001,"about_ca_system_score_gemma":0.001113601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0068844,"about_ca_topic_score_gemma":0.01686711,"domain_scores_codex":[0.99723,0.001837492,0.00008848533,0.0001051992,0.0004439256,0.0002950074],"domain_scores_gemma":[0.9950075,0.003418623,0.0005872612,0.0001467751,0.0003547987,0.0004849813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0006195491,0.0008344418,0.1901736,0.001965861,0.0001409547,0.02013068,0.5552579,0.0004965311,0.002962598,0.002881228,0.0389622,0.1855744],"study_design_scores_gemma":[0.0001087212,0.00170292,0.1567179,0.001693746,0.0002294148,0.02794374,0.7226,0.001830243,0.001123448,0.003632321,0.08218782,0.000229775],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.943269,0.004100568,0.002443536,0.01669521,0.000200775,0.000265243,0.0004246837,0.0001512249,0.03244982],"genre_scores_gemma":[0.990657,0.003098519,0.002270228,0.002029727,0.00007281526,0.00005515329,0.0001339691,0.00004811234,0.001634483],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0068844,"threshold_uncertainty_score":0.01368862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1138973791501267,"score_gpt":0.3900544851801158,"score_spread":0.2761571060299891,"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."}}