{"id":"W2169203464","doi":"10.1029/2010jg001390","title":"Ecosystem carbon dioxide fluxes after disturbance in forests of North America","year":2010,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":848,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Université Laval; Canadian Forest Service; University of British Columbia; Environment and Climate Change Canada; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ecosystem; Eddy covariance; Ecosystem respiration; Environmental science; Taiga; Carbon sink; Boreal; Temperate rainforest; Ecology; Primary production; Disturbance (geology); Forest ecology; Thinning; Chronosequence; Temperate climate; Boreal ecosystem; Carbon cycle; Temperate forest; Forestry; Geography; Biology","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":[0.0001548937,0.0001977714,0.0001827358,0.0007784732,0.0003748281,0.0005855089,0.0001122174,0.0002006218,0.0005063714],"category_scores_gemma":[0.0003967354,0.0001069203,0.0001380893,0.0008355428,0.0001670625,0.0004020962,0.0002207377,0.0001296888,0.00006656762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006976251,"about_ca_system_score_gemma":0.0002283668,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03431637,"about_ca_topic_score_gemma":0.09448514,"domain_scores_codex":[0.9999223,0.000008213779,0.000006549533,0.00002378233,0.00002290385,0.00001627512],"domain_scores_gemma":[0.9997706,0.00003221476,0.0001105558,0.0000117748,0.00004171823,0.00003310971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006031925,0.00002220258,0.9796901,0.00004580325,0.0001188542,0.0001445552,0.0002135509,0.0005883756,0.00613884,0.00003580665,0.0002704526,0.01267109],"study_design_scores_gemma":[2.247611e-7,0.000002577889,0.9996396,0.000001309619,0.000003975304,0.00002981446,0.00002379452,0.00008178591,0.00006330397,0.000007089022,0.0001454893,9.871842e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977071,0.000893563,0.0001158754,0.0000209255,0.000004875332,0.00000324647,0.0005709438,0.00001435547,0.0006690103],"genre_scores_gemma":[0.9981516,0.0005141507,0.0001805017,0.00002218676,0.000006930685,0.000006818856,0.0008205533,0.000003956241,0.0002932572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9656836,"threshold_uncertainty_score":0.06823325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007625262651223032,"score_gpt":0.257611527845872,"score_spread":0.2499862651946489,"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."}}