{"id":"W4414015726","doi":"10.11159/mvml25.108","title":"Multiple Image-Based Fire Head Detection and Contour-Based Spread Rate of Fire Head Area Estimation","year":2025,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Fire Agency; Ministry of Science and ICT, South Korea; Ministry of the Interior and Safety","keywords":"Head (geology); Computer science; Computer vision; Artificial intelligence; Fire detection; Image (mathematics); Geology; Engineering; Architectural engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006366197,0.000610247,0.0007269616,0.002508331,0.0001707423,0.0007219219,0.000773967,0.0006272675,0.001095683],"category_scores_gemma":[0.00196082,0.0003231594,0.0005715213,0.001222045,0.0002570466,0.001153624,0.0004502491,0.0005493726,0.0004985038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000449442,"about_ca_system_score_gemma":0.0003367277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003479745,"about_ca_topic_score_gemma":0.004275151,"domain_scores_codex":[0.999581,0.00003294526,0.00002390519,0.0001397382,0.0001605254,0.00006178628],"domain_scores_gemma":[0.9991986,0.0001785015,0.0001591245,0.0001059628,0.0003139708,0.00004385855],"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":[0.0006881142,0.0003250924,0.04337304,0.0002739843,0.0001899505,0.0003820646,0.0001787499,0.1265842,0.09058204,0.001052157,0.001602412,0.7347681],"study_design_scores_gemma":[0.000009452328,0.00007228,0.02444076,0.000017949,0.00004872688,0.0003543655,0.00005151205,0.9421915,0.03172776,0.0004315878,0.0006290357,0.0000251247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3800058,0.0007621928,0.6139629,0.0001131037,0.00008656966,0.0001215229,0.0005156847,0.00193276,0.002499501],"genre_scores_gemma":[0.836302,0.0003388938,0.161007,0.00003884108,0.00004098041,0.00005170489,0.0004586358,0.00008358489,0.001678463],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003479745,"threshold_uncertainty_score":0.006918967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006632180850660629,"score_gpt":0.2037342222394574,"score_spread":0.1971020413887968,"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."}}