{"id":"W2057108631","doi":"10.5558/tfc82177-2","title":"Detection of post-fire residuals using high- and medium-resolution satellite imagery","year":2006,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Energy; University of Alberta","funders":"","keywords":"Residual; Thematic Mapper; Remote sensing; Land cover; Satellite imagery; Thematic map; Environmental science; Satellite; Taiga; Physical geography; Land use; Geography; Cartography; Forestry; Computer science; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003982358,0.0001087404,0.0001239767,0.00001758066,0.0001599893,0.00002147793,0.000135106,0.00006733691,0.00007675763],"category_scores_gemma":[0.00002840889,0.00008179116,0.00003373323,0.0001603997,0.0002598844,0.0002306128,0.000118089,0.00009246618,0.00005477164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000210113,"about_ca_system_score_gemma":0.00001477273,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01539897,"about_ca_topic_score_gemma":0.00148651,"domain_scores_codex":[0.9990107,0.0001030891,0.0002183947,0.0001925798,0.0002361653,0.0002390327],"domain_scores_gemma":[0.9994563,0.0000875613,0.0001347804,0.0002772591,0.000009067308,0.00003501458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004045833,0.00003583472,0.01710498,0.00004176956,0.00000768002,0.000003916223,0.00008436597,0.002749835,0.9737018,0.00003574188,0.0001185042,0.006075085],"study_design_scores_gemma":[0.0003713004,0.0001284923,0.7234524,0.00003983617,0.00002624439,0.00004758052,0.00003659886,0.02622682,0.2485304,0.0006568116,0.0003438744,0.0001396089],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982538,0.00074131,0.0001556502,0.0001248355,0.0001228876,0.0002361361,0.00001238636,0.00003778683,0.0003152744],"genre_scores_gemma":[0.9995757,0.00001961023,0.0001818814,0.00002487005,0.0001048384,0.00000590152,0.000005266724,0.00001592965,0.00006601589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7251714,"threshold_uncertainty_score":0.9911576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005984657069154188,"score_gpt":0.20553015953952,"score_spread":0.1995455024703658,"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."}}