{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001499291,0.0002878484,0.0006524755,0.0001089642,0.00009325934,0.00004306818,0.00003314955,0.0003152517,7.808446e-7],"category_scores_gemma":[0.00004319973,0.000226158,0.0001289969,0.00007512966,0.00003412696,0.00004145866,0.00001628217,0.0001956211,0.00001093774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007786207,"about_ca_system_score_gemma":0.000008063184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008332871,"about_ca_topic_score_gemma":0.000003171291,"domain_scores_codex":[0.9990723,0.00004106975,0.0003095607,0.0002552528,0.00008421243,0.0002375648],"domain_scores_gemma":[0.9994955,0.0001781765,0.00005363012,0.0001621182,0.00001554153,0.00009504188],"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":[0.00000327251,4.175562e-7,1.43481e-7,0.003110743,0.00005759554,0.000004013235,0.00003008331,0.000009751153,0.00007983624,0.000001591486,0.000002905784,0.9966996],"study_design_scores_gemma":[0.0002347511,0.00003839794,0.00002366899,0.008434376,0.0001682833,0.0003610932,0.00002578762,0.01721515,0.0001981696,0.00000813331,0.9728426,0.0004496157],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004040464,0.9910784,0.00224942,0.0000104447,0.00147025,0.000543932,0.000009981952,0.0003308733,0.0002662821],"genre_scores_gemma":[0.007052655,0.9911785,0.0006204924,0.000001373411,0.0008724665,0.000003026444,0.000001566041,0.0001049944,0.0001649929],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.99625,"threshold_uncertainty_score":0.9222454,"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."}}