{"id":"W4281705652","doi":"10.5194/isprs-archives-xliii-b3-2022-1115-2022","title":"FIRE SEVERITY ASSESSMENT OF AN ALPINE FOREST FIRE WITH SENTINEL-2 IMAGERY","year":2022,"lang":"en","type":"article","venue":"The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Random forest; Environmental science; Satellite imagery; Remote sensing; Digital elevation model; Decision tree; Vegetation (pathology); Physical geography; Geography; Computer science; Artificial intelligence; Medicine","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":[0.0009471938,0.0003762245,0.0002110651,0.001038178,0.0001272883,0.0003904951,0.0001728154,0.0002275147,0.000429583],"category_scores_gemma":[0.0006927681,0.00009028651,0.0002701619,0.0003454399,0.00007716641,0.0002355058,0.0001686121,0.0001443823,0.0001682722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001953643,"about_ca_system_score_gemma":0.0001164058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003275882,"about_ca_topic_score_gemma":0.005551367,"domain_scores_codex":[0.9997821,0.00006022557,0.00001991088,0.00005095159,0.00006073221,0.00002604485],"domain_scores_gemma":[0.9996381,0.00006567487,0.00009922957,0.00002913321,0.0001337705,0.00003406007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008935489,0.0001990724,0.8495628,0.0001498041,0.0001544056,0.0002549401,0.0002225445,0.01592486,0.04894282,0.0001332402,0.001192937,0.08236913],"study_design_scores_gemma":[0.00002261743,0.0002656191,0.8478388,0.00003513629,0.00008983419,0.0002616859,0.0003023856,0.1406826,0.009618942,0.000101293,0.0007577328,0.00002343449],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953532,0.00007348946,0.003185303,0.00001882801,0.00001390423,0.00001627239,0.0005378036,0.00008821426,0.0007130121],"genre_scores_gemma":[0.992449,0.00005246763,0.006217461,0.00001324387,0.00001135887,0.00001285169,0.0009861103,0.000006530322,0.0002509384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003275882,"threshold_uncertainty_score":0.006513596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009847183541351131,"score_gpt":0.2427290827377511,"score_spread":0.2328818991963999,"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."}}