{"id":"W4361277442","doi":"10.3390/rs15071821","title":"Deep Learning Approaches for Wildland Fires Remote Sensing: Classification, Detection, and Segmentation","year":2023,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Fire Detection and Safety Systems","field":"Engineering","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Deep learning; Segmentation; Artificial intelligence; Market segmentation; Machine learning; Fire detection; Remote sensing; Geography; Engineering","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":[0.0008706055,0.001135771,0.0007527676,0.002052186,0.0002616552,0.001254222,0.001009479,0.001140633,0.001402812],"category_scores_gemma":[0.001453012,0.000352928,0.0009420118,0.001592482,0.0004501252,0.001289617,0.0007799875,0.001335394,0.0007680375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007807003,"about_ca_system_score_gemma":0.000790758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006762884,"about_ca_topic_score_gemma":0.008104663,"domain_scores_codex":[0.9995683,0.00007091177,0.00003771336,0.0001168518,0.0001518578,0.00005453944],"domain_scores_gemma":[0.9995978,0.0001852346,0.00005281594,0.00003483086,0.0001078729,0.00002142795],"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":[0.00008576652,0.0001434859,0.003260991,0.0009376808,0.0001786006,0.000120312,0.00009871769,0.1132469,0.009186572,0.00821171,0.01152095,0.8530084],"study_design_scores_gemma":[0.00001514932,0.0000725161,0.004106024,0.0003734289,0.000112572,0.0001945435,0.00009522976,0.937997,0.01237313,0.02275399,0.02185885,0.00004746117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02793636,0.03540127,0.923838,0.001464393,0.0003074978,0.0001140935,0.001220986,0.002101276,0.007616017],"genre_scores_gemma":[0.4345817,0.05779273,0.4904083,0.001124766,0.00079273,0.0002697199,0.005853648,0.000334214,0.008842151],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006762884,"threshold_uncertainty_score":0.01344705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03648153055778519,"score_gpt":0.2340152294937734,"score_spread":0.1975336989359882,"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."}}