{"id":"W4394819366","doi":"10.3390/fire7040140","title":"YOLO-Based Models for Smoke and Wildfire Detection in Ground and Aerial Images","year":2024,"lang":"en","type":"article","venue":"Fire","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Smoke; Firefighting; Environmental science; Vegetation (pathology); Fire detection; Terrain; Remote sensing; Computer science; Meteorology; Cartography; Geography; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003826263,0.0009226371,0.0006239238,0.0007105962,0.0002557617,0.0007621251,0.001384222,0.0007380315,0.002210629],"category_scores_gemma":[0.0008215483,0.0003199098,0.0009478096,0.0003845351,0.0003120289,0.0006978365,0.0006836238,0.0009086542,0.001099915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007022363,"about_ca_system_score_gemma":0.0008014247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02021274,"about_ca_topic_score_gemma":0.03821066,"domain_scores_codex":[0.999853,0.00001471936,0.000007154323,0.00006139464,0.00002525354,0.00003847364],"domain_scores_gemma":[0.9998136,0.00005573579,0.00002669203,0.00001736713,0.00007019334,0.00001639311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008681121,0.0004448998,0.01239434,0.0003228973,0.0002758981,0.0002032937,0.0001465056,0.4542476,0.03021632,0.00471354,0.01196995,0.4841967],"study_design_scores_gemma":[0.000008738746,0.0000322189,0.0008654727,0.00001481158,0.00001870702,0.00001918227,0.00001066443,0.9962424,0.001586701,0.0004618934,0.0007341109,0.000005171638],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2924782,0.004294815,0.6805966,0.0009190927,0.0004471176,0.0002691342,0.002222826,0.00761082,0.01116135],"genre_scores_gemma":[0.8230537,0.001390609,0.1517959,0.0009348815,0.0001958634,0.0002122374,0.005782448,0.0003174766,0.01631706],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02021274,"threshold_uncertainty_score":0.04019016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01645147607088426,"score_gpt":0.2222521695086211,"score_spread":0.2058006934377368,"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."}}