{"id":"W3037036684","doi":"","title":"Quantifying the Impacts of Disturbance on the Canadian Managed Forest Carbon Budget","year":2008,"lang":"en","type":"article","venue":"AGUFM","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Disturbance (geology); Forest degradation; Environmental science; Carbon fibers; Forestry; Environmental resource management; Geography; Agriculture; Geology; Computer science; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001276291,0.0004024252,0.0003203844,0.001275847,0.001556065,0.001810599,0.0008580883,0.0006469998,0.001469987],"category_scores_gemma":[0.004397952,0.0002359551,0.0005311268,0.002399376,0.0008488658,0.0008619718,0.0005791264,0.0005467099,0.00006741548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05507478,"about_ca_system_score_gemma":0.02988338,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9903819,"about_ca_topic_score_gemma":0.9957193,"domain_scores_codex":[0.9991905,0.0001264319,0.0000259898,0.00008888068,0.00031416,0.0002540896],"domain_scores_gemma":[0.99899,0.0002543821,0.000129198,0.00005819508,0.0004615418,0.0001065864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003539567,0.0001000939,0.4511266,0.0002023205,0.0005388272,0.0002163702,0.0002841127,0.4671148,0.003252697,0.02021906,0.005140912,0.05145017],"study_design_scores_gemma":[0.00005359329,0.0000596241,0.6249412,0.0000810641,0.0002966575,0.00006582501,0.0009409863,0.352494,0.002374895,0.006914856,0.0117025,0.00007477382],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980511,0.0008724475,0.00203552,0.00139759,0.00002187795,0.00005626209,0.002977069,0.0000490533,0.01207924],"genre_scores_gemma":[0.9965085,0.0003577131,0.001392221,0.0000672774,0.000004970178,0.00001130803,0.0005571791,0.00001093069,0.00108984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05507478,"threshold_uncertainty_score":0.3995973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02635049016830565,"score_gpt":0.2339844331923587,"score_spread":0.2076339430240531,"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."}}