{"id":"W4402474694","doi":"10.1109/ccece59415.2024.10667264","title":"Computer Vision Fire Hydrant Obstruction Detection System","year":2024,"lang":"en","type":"article","venue":"","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Computer vision; Artificial intelligence; Computer graphics (images)","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":[0.0002255505,0.0007119424,0.0007983377,0.001220689,0.0003458099,0.0006796314,0.0008891925,0.0007532449,0.006978696],"category_scores_gemma":[0.0004922145,0.0002691892,0.0006414482,0.000492516,0.0001423108,0.0005733441,0.0007930607,0.0006772159,0.00702787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005668301,"about_ca_system_score_gemma":0.0006535355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01053306,"about_ca_topic_score_gemma":0.0135225,"domain_scores_codex":[0.9996898,0.00001460811,0.00001469571,0.0001298696,0.00008833199,0.00006280024],"domain_scores_gemma":[0.9998349,0.00001033092,0.0000142894,0.00002554423,0.0001015509,0.0000132964],"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":[0.0007793818,0.000525817,0.01138907,0.0004027186,0.0001631066,0.0003915807,0.00009108496,0.0282499,0.09861822,0.001710426,0.1206344,0.7370443],"study_design_scores_gemma":[0.0001890517,0.0004238068,0.0301025,0.00008051873,0.0001209019,0.0009259596,0.0001662436,0.8050523,0.09015871,0.002964769,0.06970785,0.0001074242],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2240529,0.001906174,0.6071489,0.0005467555,0.0006948009,0.00166168,0.02549884,0.09472427,0.04376565],"genre_scores_gemma":[0.6131849,0.0007473237,0.3024019,0.0006930161,0.0001455,0.0008408467,0.05822169,0.0007651942,0.02299958],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01053306,"threshold_uncertainty_score":0.02334607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003828337438896632,"score_gpt":0.1802350084317702,"score_spread":0.1764066709928735,"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."}}