{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003417856,0.0005488058,0.0001981513,0.0002431174,0.0002038605,0.0005271801,0.0005757001,0.0005991525,0.006396771],"category_scores_gemma":[0.001118807,0.0001606181,0.0001687631,0.00009895097,0.000399815,0.0009805177,0.0008126996,0.0003198707,0.0008407916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001119347,"about_ca_system_score_gemma":0.0002608208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003937096,"about_ca_topic_score_gemma":0.000525261,"domain_scores_codex":[0.9998457,0.00003354244,0.000005953245,0.00002489299,0.00007339491,0.00001646032],"domain_scores_gemma":[0.9997707,0.00009825692,0.00002544495,0.00003142661,0.00004602206,0.00002821187],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001789879,0.0004663003,0.003267287,0.001020736,0.00005885754,0.0007786059,0.001160932,0.0131851,0.5850527,0.006289734,0.01065912,0.3762708],"study_design_scores_gemma":[0.001460501,0.01547073,0.03527244,0.0005133883,0.0003216778,0.006484126,0.002301718,0.4009348,0.4137397,0.0135587,0.1094757,0.0004664534],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.203568,0.0006007663,0.7753366,0.0005392961,0.0004642112,0.0003204242,0.0003861806,0.007158938,0.01162556],"genre_scores_gemma":[0.8384078,0.0003290654,0.150882,0.0003371985,0.0001083676,0.0001796753,0.000233173,0.000222646,0.009300049],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006396771,"threshold_uncertainty_score":0.02139932,"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."}}