{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001029897,0.0008546046,0.0003308229,0.0004068127,0.0003103586,0.0007574705,0.0005428352,0.0005197268,0.001516019],"category_scores_gemma":[0.001685958,0.0002389658,0.0005357077,0.0004624173,0.0002350982,0.000489958,0.0003063503,0.0002840222,0.000343481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008631484,"about_ca_system_score_gemma":0.0007890373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07058185,"about_ca_topic_score_gemma":0.04880367,"domain_scores_codex":[0.999815,0.00007013883,0.00001412694,0.00005684649,0.00002403985,0.00001972104],"domain_scores_gemma":[0.9991913,0.0004271748,0.00008615768,0.00009903456,0.000137607,0.00005877539],"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":[0.0004918491,0.0001652347,0.08888404,0.0000464009,0.0002904438,0.00006247742,0.00006787301,0.8978947,0.001904061,0.0003019166,0.001906,0.007985073],"study_design_scores_gemma":[0.0001247167,0.0001684795,0.03646237,0.00001492359,0.00008010081,0.00002183172,0.00006230688,0.9602232,0.001920227,0.0001854822,0.0007147088,0.00002155927],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952651,0.0000996567,0.0008285436,0.0001127583,0.0000148753,0.0000110261,0.001225946,0.0004207027,0.002021452],"genre_scores_gemma":[0.9976553,0.00004342298,0.0006998846,0.00001715223,0.000003934743,0.00001346161,0.001223849,0.00004295619,0.000300095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07058185,"threshold_uncertainty_score":0.1403421,"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."}}