{"id":"W4391096871","doi":"10.1109/gem59776.2023.10390296","title":"Safety Sense: Haptic Navigation for Emergency Responders in Obscured Visibility Environments","year":2023,"lang":"en","type":"article","venue":"","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Haptic technology; Visibility; Computer science; Wearable computer; Situation awareness; Path (computing); Motion planning; Human–computer interaction; Simulation; Emergency response; Wearable technology; Real-time computing; Robot; Computer vision; Artificial intelligence; Engineering; Embedded system; Computer network; Aerospace engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0002722626,0.00007661479,0.00007549686,0.00006850273,0.00002966522,0.000005596688,0.00003898246,0.00005938461,0.0001481572],"category_scores_gemma":[0.00003955829,0.00008208196,0.00003776521,0.0002348354,0.000007932104,0.00008071393,0.00001064305,0.00005676458,0.0001301733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001067106,"about_ca_system_score_gemma":0.000005211976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005247086,"about_ca_topic_score_gemma":0.00005365639,"domain_scores_codex":[0.9993601,0.00001706708,0.0002356734,0.0001294688,0.0001015362,0.0001561552],"domain_scores_gemma":[0.9997571,0.00004249911,0.00001290476,0.0001477546,0.000006243306,0.00003351269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001885377,0.00009777856,0.01486665,0.0003542853,0.00009058323,0.00001176287,0.002695126,0.8541046,0.1005515,0.008522835,0.006109569,0.01240685],"study_design_scores_gemma":[0.0003852067,0.00001091294,0.07971768,0.000006334405,0.000003964207,3.302977e-7,0.0002219217,0.9158645,0.0003338202,0.001795371,0.001547988,0.000112025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8993353,0.00001968828,0.09806009,0.0001941313,0.0003510482,0.0004134305,0.00002381786,0.0003373072,0.001265133],"genre_scores_gemma":[0.9967714,0.00006213588,0.0005665695,0.00001176794,0.00001369153,0.00002823567,0.0001597103,0.00001894276,0.002367552],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1002176,"threshold_uncertainty_score":0.3347205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01615135955014225,"score_gpt":0.2659956391925266,"score_spread":0.2498442796423843,"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."}}