{"id":"W2796299567","doi":"10.1109/tie.2018.2823658","title":"Kalman Filter-Based Large-Scale Wildfire Monitoring With a System of UAVs","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Electronics","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":115,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"China Scholarship Council","keywords":"Kalman filter; Computer science; Scale (ratio); Ensemble Kalman filter; Extended Kalman filter; Environmental science; Remote sensing; Artificial intelligence; 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":[0.0003376754,0.0004506001,0.0004891621,0.0003419174,0.0003094633,0.0003503244,0.0004743071,0.0003361409,0.0006146148],"category_scores_gemma":[0.0008765921,0.0002341068,0.000254837,0.0003147679,0.0002033403,0.000791725,0.0003892914,0.0003785446,0.0001919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003774616,"about_ca_system_score_gemma":0.0005896332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01244461,"about_ca_topic_score_gemma":0.01331931,"domain_scores_codex":[0.999801,0.00003051512,0.00001501988,0.00007861001,0.00005239508,0.00002244412],"domain_scores_gemma":[0.9997571,0.00008117895,0.00004698461,0.00003273239,0.00006949712,0.0000124862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003302379,0.0001374334,0.00887446,0.0001823463,0.0001547795,0.0001865401,0.0002034336,0.5907535,0.05253463,0.003692234,0.001863218,0.3410871],"study_design_scores_gemma":[0.0000119854,0.00006155854,0.002326154,0.000006318684,0.00001930122,0.00002858139,0.00001460179,0.9914429,0.004849529,0.0005810991,0.0006474492,0.00001058901],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06590135,0.0002574004,0.9314482,0.00005795308,0.00004407051,0.00003487584,0.0001003799,0.0009360111,0.00121979],"genre_scores_gemma":[0.9183297,0.0001571272,0.0802301,0.00002936263,0.00001909655,0.00005206719,0.0001485823,0.00002089082,0.001013228],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01244461,"threshold_uncertainty_score":0.02474433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01371247431311716,"score_gpt":0.2194711590430704,"score_spread":0.2057586847299533,"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."}}