{"id":"W2508764147","doi":"10.3390/s16081310","title":"Airborne Optical and Thermal Remote Sensing for Wildfire Detection and Monitoring","year":2016,"lang":"en","type":"review","venue":"Sensors","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":298,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Canadian Forest Service; York University","funders":"Ontario Centres of Excellence","keywords":"Drone; Remote sensing; Fire detection; Hyperspectral imaging; Context (archaeology); Computer science; Systems engineering; Environmental science; Environmental monitoring; Engineering; Architectural engineering; Geography","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":[0.0007668582,0.0009060109,0.0007666876,0.002481295,0.0002888743,0.0009432197,0.0007673823,0.00121045,0.005331131],"category_scores_gemma":[0.0007053929,0.0003143564,0.0006905852,0.00257231,0.0004784983,0.001354141,0.0006972605,0.001076658,0.002866808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000454201,"about_ca_system_score_gemma":0.0007584665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001019881,"about_ca_topic_score_gemma":0.001824811,"domain_scores_codex":[0.9995981,0.00005124842,0.00002850131,0.00008249281,0.0002088031,0.00003091749],"domain_scores_gemma":[0.9995542,0.0001977557,0.00006880725,0.00002025651,0.0001396231,0.00001932356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002990319,0.00009649094,0.0004869667,0.01272781,0.00007885769,0.0001269534,0.00006119776,0.00112944,0.008632372,0.009132486,0.01335736,0.9541402],"study_design_scores_gemma":[0.000004846178,0.0001404238,0.001653387,0.003482803,0.00010378,0.0009906552,0.0001033865,0.0007648703,0.005177899,0.00492914,0.9826128,0.00003593386],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0007402338,0.9881949,0.002760873,0.0003377686,0.0002852741,0.00001967282,0.00005293997,0.00002236019,0.007585891],"genre_scores_gemma":[0.007580395,0.9858159,0.002561491,0.0002133686,0.0002327255,0.00001742449,0.00008255609,0.00000723859,0.003489027],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005331131,"threshold_uncertainty_score":0.01783442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02214395972269058,"score_gpt":0.2603073152471543,"score_spread":0.2381633555244637,"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."}}