{"id":"W2166703347","doi":"10.1139/x08-185","title":"Composition and carbon dynamics of forests in northeastern North America in a future, warmer worldThis article is one of a selection of papers from NE Forests 2100: A Synthesis of Climate Change Impacts on Forests of the Northeastern US and Eastern Canada.","year":2009,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Plant responses to elevated CO2","field":"Agricultural and Biological Sciences","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"Canadian Forest Service; Northeastern States Research Cooperative; Natural Resources Canada; U.S. Department of Energy; U.S. Forest Service; National Science Foundation","keywords":"Climate change; Environmental science; Ecology; Global warming; Habitat; Carbon sequestration; Forest ecology; Ecosystem; Carbon dioxide; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0004161771,0.0001478855,0.0004713505,0.0002912314,0.00005371795,0.00001321799,0.0002785562,0.00008950374,0.00001623732],"category_scores_gemma":[0.0001116454,0.00007742165,0.00006725406,0.0009947392,0.0002418714,0.0001016245,0.00003194409,0.0003026672,6.910322e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000181889,"about_ca_system_score_gemma":0.0003550513,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7514074,"about_ca_topic_score_gemma":0.9993305,"domain_scores_codex":[0.997861,0.0002837872,0.00064053,0.0001749436,0.0005863011,0.000453412],"domain_scores_gemma":[0.9984157,0.0003762216,0.0005112884,0.0001024277,0.0003077637,0.0002865659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009705244,0.00009087462,0.9604977,0.00005716239,0.00002792557,0.00002326415,0.0004767979,0.0001438146,0.005214461,0.000008792678,0.00000201552,0.03248666],"study_design_scores_gemma":[0.0003825237,0.0009002252,0.9920478,0.0008219143,0.00002288828,0.00001974292,0.0002683399,0.002269065,0.003096387,0.00007551902,0.000008641587,0.00008689729],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977732,0.0002572707,1.277353e-7,0.001175224,0.00002151738,0.000319058,0.0004097616,9.254727e-7,0.00004290784],"genre_scores_gemma":[0.9997328,0.0001682404,0.00000837384,0.00003150795,0.00003806505,0.000004241393,0.00001116664,0.000003051896,0.00000254322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2479231,"threshold_uncertainty_score":0.3157163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01885874151033521,"score_gpt":0.2322007521567304,"score_spread":0.2133420106463952,"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."}}