{"id":"W2154965974","doi":"10.1186/s40663-015-0039-2","title":"Holocene variations of wildfire occurrence as a guide for sustainable management of the northeastern Canadian boreal forest","year":2015,"lang":"en","type":"article","venue":"Forest Ecosystems","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Université du Québec en Abitibi-Témiscamingue; Université du Québec à Montréal; Canadian Forest Service; Natural Sciences and Engineering Research Council of Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Centre National de la Recherche Scientifique","keywords":"Holocene; Charcoal; Environmental science; Fire regime; Radiocarbon dating; Taiga; Physical geography; Climate change; Boreal; Woodland; Fire history; Ecosystem; Forestry; Ecology; Geography; Geology; Oceanography; Archaeology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007997344,0.0004357894,0.0001647464,0.00321934,0.001566278,0.0009639435,0.0008321535,0.0002084005,0.002252331],"category_scores_gemma":[0.001103229,0.0001388591,0.0001921516,0.002279632,0.0003104258,0.0002341238,0.0003411963,0.0003878815,0.0003310153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01176186,"about_ca_system_score_gemma":0.008863769,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9724452,"about_ca_topic_score_gemma":0.9953195,"domain_scores_codex":[0.9997323,0.00003004128,0.00002647445,0.00003852271,0.0001043642,0.0000682251],"domain_scores_gemma":[0.9986221,0.00005742757,0.0001827936,0.00003101092,0.0009063419,0.0002005094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001199885,0.00006339058,0.8368437,0.0002045063,0.00007408438,0.0001661713,0.001852053,0.002501652,0.002376241,0.0004845997,0.03229639,0.1230173],"study_design_scores_gemma":[0.000004017342,0.00001679098,0.980382,0.00006657183,0.0000122077,0.00003780256,0.001365172,0.001213799,0.0002046944,0.00004948246,0.01663322,0.00001420412],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8901206,0.008149857,0.01029732,0.002024396,0.0001790809,0.0006680521,0.0452517,0.001096299,0.04221259],"genre_scores_gemma":[0.9440076,0.002047287,0.02919045,0.0002111748,0.00003630176,0.0002280633,0.01283443,0.00008398722,0.01136073],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02755481,"threshold_uncertainty_score":0.08533865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008795777690102565,"score_gpt":0.2199561118308996,"score_spread":0.211160334140797,"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."}}