{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001952431,0.000186734,0.0001823843,0.0001939084,0.0001198779,0.0000515257,0.00004950612,0.00009169133,0.000003911068],"category_scores_gemma":[0.0001625125,0.0001983851,0.00004287802,0.0003761628,0.00002250903,0.0001327576,0.00006558898,0.0002220683,0.00002381451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000713,"about_ca_system_score_gemma":0.000007986077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001678215,"about_ca_topic_score_gemma":0.000001303119,"domain_scores_codex":[0.9990824,0.00003929081,0.0001792703,0.000228786,0.0001821888,0.0002880483],"domain_scores_gemma":[0.9994167,0.0002085739,0.00003019851,0.0002258628,0.0000405032,0.00007814156],"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":[0.000009287722,0.000002028174,0.00001807422,0.00006002374,0.000004003271,0.00008492019,0.00008243811,0.01228371,0.3537948,7.968771e-7,0.0002749815,0.6333849],"study_design_scores_gemma":[0.0001261122,0.00002657991,0.0005067659,0.0002430742,0.000005399345,0.000008883579,0.00004938805,0.8077677,0.1902602,0.0003690491,0.0004692828,0.0001675907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4056099,0.0000503369,0.5891628,0.00005327684,0.0002876527,0.0001873596,0.000002340138,0.00275256,0.001893773],"genre_scores_gemma":[0.4039812,0.000122776,0.5954295,0.000036676,0.0001851091,8.218618e-8,0.00001043571,0.00009950293,0.000134657],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7954839,"threshold_uncertainty_score":0.8089909,"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."}}