{"id":"W1968644285","doi":"10.1111/j.1600-0889.2006.00206.x","title":"Estimating regional carbon exchange in New England and Quebec by combining atmospheric, ground-based and satellite data","year":2006,"lang":"en","type":"article","venue":"Tellus B","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of Wyoming; National Aeronautics and Space Administration; National Oceanic and Atmospheric Administration; National Science Foundation","keywords":"Eddy covariance; Environmental science; Biosphere; Flux (metallurgy); Atmospheric model; Vegetation (pathology); Climatology; Atmospheric sciences; Meteorology; Geography; Geology; Ecosystem","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.0001716381,0.0001670125,0.0001485463,0.000001992226,0.0000711047,0.00003815568,0.0001660515,0.00006864617,0.00008880458],"category_scores_gemma":[0.000007133893,0.0001674792,0.000009595747,0.00009999142,0.0002361235,0.0001385951,0.0002936321,0.0001081151,0.000005818963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001329466,"about_ca_system_score_gemma":0.00001121046,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.107283,"about_ca_topic_score_gemma":0.0164521,"domain_scores_codex":[0.9989211,0.00003454651,0.0001821008,0.0004223606,0.0001854399,0.000254465],"domain_scores_gemma":[0.9995097,0.00005896862,0.00006748024,0.0002684404,6.31458e-7,0.00009479575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003765519,0.00008558042,0.839621,0.00002126007,0.000005008086,0.00002175003,0.0004763576,0.01912976,0.0007798236,0.00001719138,0.0007060525,0.1390985],"study_design_scores_gemma":[0.001485877,0.0000583305,0.34392,0.00002855491,0.00001401404,0.0000169389,0.00007283279,0.6343488,0.00001040078,0.0002391833,0.01949101,0.0003141534],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927139,0.001222045,0.004535091,0.0001783137,0.0000384472,0.0001357384,0.000002757751,0.00002830245,0.001145422],"genre_scores_gemma":[0.9278344,0.0001149968,0.06915906,0.0002528214,0.00006582738,0.000003879279,0.00009298701,0.00002874051,0.002447283],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.615219,"threshold_uncertainty_score":0.9180659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01190918463726635,"score_gpt":0.2049228443408877,"score_spread":0.1930136597036213,"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."}}