{"id":"W2143941656","doi":"10.1002/2013jg002553","title":"Comprehensive ecosystem model‐data synthesis using multiple data sets at two temperate forest free‐air CO<sub>2</sub> enrichment experiments: Model performance at ambient CO<sub>2</sub> concentration","year":2014,"lang":"en","type":"article","venue":"Journal of Geophysical Research Biogeosciences","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":121,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"Oak Ridge National Laboratory; Biological and Environmental Research; Office of Science; National Center for Ecological Analysis and Synthesis; UT-Battelle; Battelle; National Centre for Earth Observation; U.S. Department of Energy","keywords":"Evergreen; Transpiration; Leaf area index; Temperate rainforest; Environmental science; Temperate forest; Canopy; Deciduous; Range (aeronautics); Temperate deciduous forest; Forest ecology; Primary production; Temperate climate; Basal area; Atmospheric sciences; Ecosystem; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.002583078,0.001085698,0.0009869087,0.000454935,0.0006304894,0.0008220691,0.0008385609,0.001025195,0.0009642738],"category_scores_gemma":[0.0036479,0.0004918927,0.001308579,0.0004425719,0.000368541,0.0009064638,0.0005814925,0.0008594319,0.0001263867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001262565,"about_ca_system_score_gemma":0.0008244182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02444088,"about_ca_topic_score_gemma":0.02153723,"domain_scores_codex":[0.9995317,0.0002261968,0.00005172827,0.0001033349,0.00004825037,0.00003876612],"domain_scores_gemma":[0.9973248,0.001741577,0.0001346293,0.0002809353,0.0004449624,0.00007307195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000782229,0.0004743337,0.03826724,0.000147785,0.0004332423,0.000125844,0.00008700651,0.9464197,0.006347504,0.0004073624,0.0004447357,0.006063072],"study_design_scores_gemma":[0.0002107515,0.000418415,0.02036584,0.00001332754,0.0001523371,0.0000166563,0.0001034137,0.968141,0.009735554,0.0004025053,0.000386357,0.00005383317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99485,0.00005193871,0.002928759,0.00006546279,0.000007278862,0.00006917718,0.001387531,0.0001594343,0.0004804576],"genre_scores_gemma":[0.9926916,0.00002374579,0.005453745,0.00002878712,0.000003645569,0.0001282322,0.001512398,0.00002440307,0.0001334796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02444088,"threshold_uncertainty_score":0.04859722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0769242972206749,"score_gpt":0.3234382322713698,"score_spread":0.2465139350506949,"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."}}