{"id":"W2102096266","doi":"10.1111/j.1365-2486.2012.02678.x","title":"Terrestrial biosphere model performance for inter‐annual variability of land‐atmosphere <scp><scp>CO<sub>2</sub></scp></scp> exchange","year":2012,"lang":"en","type":"article","venue":"Global Change Biology","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":284,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of Alberta","funders":"Office of Science; U.S. Department of Energy","keywords":"Biosphere; Eddy covariance; Biosphere model; Environmental science; Atmosphere (unit); Atmospheric sciences; Snowpack; Climatology; Abiotic component; Flux (metallurgy); Climate model; Range (aeronautics); Ecosystem; Climate change; Snow; Meteorology; Ecology; Geography; Geology; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006210175,0.0004956567,0.0005615468,0.000004574392,0.0001629431,0.00001370422,0.0005919331,0.0005643461,0.00009616779],"category_scores_gemma":[0.0002256651,0.000444338,0.000228964,0.0002509623,0.0007032612,0.0004709768,0.0005995139,0.0002154021,0.000173183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005545364,"about_ca_system_score_gemma":0.00002151388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003905698,"about_ca_topic_score_gemma":0.0000909153,"domain_scores_codex":[0.9971594,0.0001517137,0.0005249567,0.0006827218,0.0002539423,0.001227235],"domain_scores_gemma":[0.9985228,0.0002527221,0.0003375944,0.0005172232,0.00001339644,0.0003562468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005846574,0.0004627978,0.9657508,0.00008051575,0.00007063977,0.000001214258,0.001225343,0.001613979,0.001478015,0.00009594642,0.003980044,0.02518227],"study_design_scores_gemma":[0.006235269,0.003312916,0.6298882,0.0001071716,0.0003999247,0.00009580167,0.003086425,0.232612,0.003986037,0.002643161,0.1167568,0.0008761847],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.979358,0.0003709584,0.01422986,0.00003129778,0.0008610199,0.000888125,0.0006372834,0.00008704646,0.003536468],"genre_scores_gemma":[0.9918833,0.0003274065,0.006227893,0.0003217279,0.0005734362,0.0002352864,0.0001561269,0.00004032807,0.0002345196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3358625,"threshold_uncertainty_score":0.9998009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01923677063787395,"score_gpt":0.2416794987789929,"score_spread":0.2224427281411189,"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."}}