{"id":"W4416038936","doi":"10.1016/j.geomat.2025.100083","title":"Corrigendum to “Trends and applications in wildfire burned area mapping: Remote sensing data, cloud geoprocessing platforms, and emerging algorithms” [Geomatica 76 (2024) 100008]","year":2025,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Geoprocessing; Cloud computing; Remote sensing application; Reflectivity","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007025028,0.0003073019,0.0004192024,0.0002962408,0.000395898,0.0001787987,0.0004002115,0.0001210989,0.0001146469],"category_scores_gemma":[0.0001551779,0.0002926604,0.00002504577,0.001258742,0.0001407669,0.0003980029,0.0008705822,0.0002144269,0.00007521863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001687352,"about_ca_system_score_gemma":0.00002745367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001550275,"about_ca_topic_score_gemma":0.0006767304,"domain_scores_codex":[0.9976845,0.00004304958,0.0005782189,0.0008007542,0.0003280005,0.0005654562],"domain_scores_gemma":[0.9986057,0.0001617486,0.000147468,0.0008625329,0.000009446478,0.0002130847],"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":[0.00001580204,0.00007404099,0.01385848,0.0004471742,0.00005350203,0.00003606095,0.002490985,0.0001008992,0.001096839,0.00007752204,0.006779115,0.9749696],"study_design_scores_gemma":[0.0005810731,0.00004659402,0.05738785,0.0008384409,0.00006226782,0.00008149081,0.001479096,0.9075166,0.0001090465,0.003027755,0.02829794,0.0005718321],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8546818,0.0005107544,0.1259599,0.001874326,0.0007575633,0.001440899,0.00005808608,0.0002630809,0.01445354],"genre_scores_gemma":[0.9546542,0.00003591736,0.0410536,0.0004751599,0.0001078384,0.00002288643,0.0001048804,0.000050244,0.003495324],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9743978,"threshold_uncertainty_score":0.9999526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0172531863821562,"score_gpt":0.2532055022482313,"score_spread":0.2359523158660751,"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."}}