{"id":"W4381166131","doi":"10.3390/rs15123173","title":"Forest Fire Monitoring Method Based on UAV Visual and Infrared Image Fusion","year":2023,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Advanced Image Fusion Techniques","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Energy, Northern Development and Mines","funders":"National Natural Science Foundation of China","keywords":"Remote sensing; ALARM; Constant false alarm rate; Computer science; Environmental science; Image fusion; Warning system; Aerial photography; False alarm; Sensor fusion; Artificial intelligence; Computer vision; Image (mathematics); Geography","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":[0.0004262965,0.000514854,0.0004683151,0.001092543,0.000245155,0.0003715097,0.0003628389,0.0003459401,0.0003938655],"category_scores_gemma":[0.0006553749,0.0001733837,0.0004426738,0.0005091805,0.0001539838,0.0007283297,0.0004273042,0.0003288923,0.0001291981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003129095,"about_ca_system_score_gemma":0.0002309128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00269885,"about_ca_topic_score_gemma":0.00276552,"domain_scores_codex":[0.9996727,0.00003814825,0.00001600756,0.0001001321,0.0001240127,0.00004910024],"domain_scores_gemma":[0.999835,0.00002826383,0.00002940555,0.00001698227,0.00007708505,0.00001312056],"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":[0.0007373869,0.0002626092,0.01436457,0.0001814849,0.0001793086,0.0002561032,0.0001665094,0.1006036,0.1667772,0.001410475,0.00137323,0.7136875],"study_design_scores_gemma":[0.00001508555,0.000187861,0.01532103,0.000017049,0.0001008564,0.0003070268,0.00006695593,0.9355267,0.04685052,0.0006768251,0.0009010549,0.00002909558],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3897455,0.001042761,0.6039193,0.0001234442,0.0001387675,0.0001105208,0.000210447,0.001045867,0.003663429],"genre_scores_gemma":[0.9241911,0.0002039004,0.07466361,0.00003817698,0.00002768121,0.0000279795,0.0001298395,0.00001055004,0.0007071685],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00269885,"threshold_uncertainty_score":0.005366266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01179776098909006,"score_gpt":0.2975829797999026,"score_spread":0.2857852188108125,"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."}}