{"id":"W2097352499","doi":"10.1016/j.ecolmodel.2009.11.024","title":"Comparing measured and modelled forest carbon stocks in high-boreal forests of harvest and natural-disturbance origin in Labrador, Canada","year":2009,"lang":"en","type":"article","venue":"Ecological Modelling","topic":"Forest Ecology and Biodiversity Studies","field":"Agricultural and Biological Sciences","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"Department of Natural Resources, Government of Newfoundland and Labrador","keywords":"Coarse woody debris; Bryophyte; Environmental science; Chronosequence; Taiga; Snag; Carbon stock; Black spruce; Disturbance (geology); Forest floor; Forest ecology; Ecosystem; Forestry; Debris; Boreal; Podzol; Biomass (ecology); Ecology; Atmospheric sciences; Soil science; Climate change; Soil water; Geology; Geography; Biology; Habitat; Oceanography","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":[0.0006461962,0.0004515632,0.0003621253,0.0007367876,0.001229058,0.001611029,0.001454237,0.0004286021,0.001038381],"category_scores_gemma":[0.001332217,0.0003288851,0.0005792875,0.001296358,0.000762214,0.0004920325,0.000407556,0.0003242621,0.0001243582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0228387,"about_ca_system_score_gemma":0.01044086,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9924811,"about_ca_topic_score_gemma":0.9938444,"domain_scores_codex":[0.9996554,0.00006179842,0.00002565613,0.00007797396,0.00005575423,0.0001234473],"domain_scores_gemma":[0.9992998,0.0001646498,0.00007488613,0.00003478821,0.0002915162,0.0001343724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00113192,0.0002492116,0.7579302,0.0001654515,0.0005650059,0.0004021075,0.0009560278,0.2193201,0.003152861,0.001018198,0.001594282,0.01351466],"study_design_scores_gemma":[0.0001972992,0.00007329711,0.7815426,0.00005020753,0.0001717323,0.000127775,0.001959274,0.2121713,0.002025218,0.0002475394,0.001308754,0.000125014],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983979,0.00007273743,0.0001622488,0.0000341354,0.000002189938,0.000009721241,0.0007833772,0.0000263493,0.0005114383],"genre_scores_gemma":[0.9990314,0.00003412089,0.0002213875,0.00000845103,6.470654e-7,0.0000049734,0.0004562976,0.000005094434,0.0002376564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0228387,"threshold_uncertainty_score":0.1657072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02539004281875635,"score_gpt":0.1942139942262977,"score_spread":0.1688239514075414,"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."}}