{"id":"W4403024206","doi":"10.1109/iccims61672.2024.10690685","title":"Drone Assist Indoor Locating System for Trapped Victim Using Smartphone Application in a 3D Space","year":2024,"lang":"en","type":"article","venue":"","topic":"IoT and GPS-based Vehicle Safety Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Drone; Computer science; Space (punctuation); Embedded system; Computer security; Human–computer interaction; Operating system","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":[0.0001151928,0.0007554337,0.0006386117,0.000628603,0.0003047736,0.0005603445,0.0008095996,0.0005346541,0.007975305],"category_scores_gemma":[0.0003832711,0.0001951273,0.000387398,0.0001947082,0.0001497281,0.0006818888,0.001088783,0.0002643545,0.00216363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001106766,"about_ca_system_score_gemma":0.0002421894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001478931,"about_ca_topic_score_gemma":0.002431794,"domain_scores_codex":[0.999819,0.00002380038,0.00001167545,0.00003717628,0.00007462418,0.00003381484],"domain_scores_gemma":[0.9998586,0.00002084024,0.0000149733,0.00002318456,0.00005403098,0.00002829114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002051017,0.0006497486,0.0282566,0.002338562,0.0002912887,0.01166476,0.004840733,0.01167786,0.2559427,0.003629974,0.0971252,0.5815316],"study_design_scores_gemma":[0.0009301356,0.004904905,0.08956442,0.0009531044,0.001081422,0.02026056,0.007504181,0.2821531,0.21537,0.00434195,0.3720479,0.000888335],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.515104,0.004974688,0.3709928,0.001369412,0.001131247,0.001101862,0.00394616,0.04572905,0.0556507],"genre_scores_gemma":[0.9344417,0.0012156,0.03898486,0.0004762383,0.0001007183,0.000381125,0.001459385,0.0002214243,0.02271894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007975305,"threshold_uncertainty_score":0.02668005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01017661170036867,"score_gpt":0.2320682743886593,"score_spread":0.2218916626882906,"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."}}