{"id":"W2158006920","doi":"10.1016/j.foreco.2014.12.027","title":"Differentiating mixed- and high-severity fire regimes in mixed-conifer forests of the Canadian Cordillera","year":2015,"lang":"en","type":"article","venue":"Forest Ecology and Management","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":52,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; University of British Columbia","funders":"","keywords":"Larch; Forest structure; Ecology; Geography; Fire regime; Disturbance (geology); Snag; Fire history; Physical geography; Fire ecology; Forestry; Pinus contorta; Environmental science; Habitat; Ecosystem; Biology; Climate change; Canopy","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003419829,0.0001102128,0.0001681797,0.00004125002,0.0001313475,0.00001676957,0.0001588815,0.00008956389,0.00005591907],"category_scores_gemma":[0.0000424244,0.00008431062,0.00001784963,0.0001017885,0.0001918486,0.00008661229,0.0003485289,0.00009692802,0.00001718263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001725995,"about_ca_system_score_gemma":0.00001454518,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08508454,"about_ca_topic_score_gemma":0.9289184,"domain_scores_codex":[0.999099,0.00010886,0.0001698201,0.0002301197,0.0001275059,0.0002646727],"domain_scores_gemma":[0.9995487,0.00004735695,0.0000810767,0.000200525,0.000005626624,0.0001167691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009232319,0.00003160687,0.9919411,0.00005100983,0.00001967963,0.00001631624,0.0001545503,0.0001337116,0.00000160289,0.001457377,0.003026809,0.003157003],"study_design_scores_gemma":[0.0004978356,0.00006853962,0.9926037,0.00002579556,0.00001737722,0.000004852976,0.0000787669,0.003796964,0.0000162313,0.001323007,0.001475638,0.00009133438],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950346,0.00004105807,0.000004636997,0.0005609595,0.0003989168,0.0005210442,0.000005437235,0.000008230417,0.003425132],"genre_scores_gemma":[0.9992522,0.00001500843,0.00008634389,0.0001232633,0.00001045235,0.00004984807,0.000004195247,0.000007420739,0.0004512852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8438339,"threshold_uncertainty_score":0.9210079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006303322165966203,"score_gpt":0.1875251400875506,"score_spread":0.1812218179215844,"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."}}