{"id":"W4392864560","doi":"10.1080/01431161.2024.2326534","title":"Characterizing post-fire northern boreal forest height dynamics","year":2024,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Space Agency","keywords":"Taiga; Boreal; Environmental science; Remote sensing; Fire regime; Physical geography; Geography; Meteorology; Ecology; Forestry; Ecosystem","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.0004003964,0.0001396244,0.0001637548,0.0001084043,0.00004721412,0.0002042133,0.0003006782,0.00006198214,0.00004758462],"category_scores_gemma":[0.000103582,0.0001183393,0.0001592674,0.0001185136,0.00005166695,0.0004854512,0.0001081987,0.0002921387,0.0001959824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008404813,"about_ca_system_score_gemma":0.00003713898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001355328,"about_ca_topic_score_gemma":0.003232716,"domain_scores_codex":[0.9984838,0.00005114001,0.0004162565,0.0001701271,0.000692511,0.0001862103],"domain_scores_gemma":[0.9993584,0.0001065495,0.0002251983,0.0001093654,0.0001056457,0.00009491269],"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":[0.00004438069,0.00001195471,0.00447904,0.00001281364,0.0001106696,0.001743706,0.0004475542,0.0001975982,0.01055288,0.00001958427,0.0001791219,0.9822007],"study_design_scores_gemma":[0.0002656577,0.0001204619,0.05121949,0.0007687524,0.00003172986,0.006092273,0.0001122449,0.924893,0.000995121,0.0003842445,0.01488904,0.0002279474],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9798946,0.0001027037,0.009039432,0.0031771,0.003668039,0.00006631601,0.0000100337,0.00003773414,0.004004013],"genre_scores_gemma":[0.9944097,0.00002147125,0.004398244,0.0002389611,0.000736894,1.449432e-8,0.00001391796,0.00003178732,0.000149012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9819728,"threshold_uncertainty_score":0.4825738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00496521121648808,"score_gpt":0.2239683013471609,"score_spread":0.2190030901306728,"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."}}