{"id":"W2110970138","doi":"10.1175/2010ei319.1","title":"Satellite-Based Modeling of the Carbon Fluxes in Mature Black Spruce Forests in Alaska: A Synthesis of the Eddy Covariance Data and Satellite Remote Sensing Data","year":2010,"lang":"en","type":"article","venue":"Earth Interactions","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Aeronautics and Space Administration","keywords":"Environmental science; Eddy covariance; Carbon cycle; Carbon sink; Normalized Difference Vegetation Index; Moderate-resolution imaging spectroradiometer; Primary production; Atmospheric sciences; Climatology; Ecosystem respiration; Leaf area index; Satellite; Climate change; Ecosystem; Ecology; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003103005,0.00009408136,0.0001252749,0.00004495034,0.0000479671,0.00002165971,0.0005110359,0.00006124907,0.0000132857],"category_scores_gemma":[0.0001622668,0.00006404344,0.00002187106,0.0002831962,0.0001505488,0.0002164656,0.0004759483,0.0003842217,0.000002103171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000173937,"about_ca_system_score_gemma":0.00002254606,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002313833,"about_ca_topic_score_gemma":0.08453807,"domain_scores_codex":[0.99908,0.00008771891,0.0002740278,0.0002697966,0.0001566449,0.0001318239],"domain_scores_gemma":[0.998491,0.0001735976,0.0001230206,0.001181483,0.000007890801,0.00002298446],"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":[0.00007943949,0.0001112506,0.2659611,0.00005401843,0.00002885082,0.000006286602,0.001311221,0.6528125,0.04940607,0.00005121489,0.00001335516,0.03016466],"study_design_scores_gemma":[0.00008339741,0.00000238258,0.07126582,0.0001569976,0.00001492342,0.000009195435,0.00003259881,0.9263631,0.001386776,0.0001824746,0.0004400983,0.00006231148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997484,0.00002343396,0.0007555115,0.000469119,0.0001830037,0.0001747848,0.0001813228,0.000005386397,0.0007234453],"genre_scores_gemma":[0.9941883,0.00003858019,0.005628823,0.00002848139,0.00001108852,3.536175e-7,0.00002667924,0.000008137828,0.00006952728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2735505,"threshold_uncertainty_score":0.9321667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01900062886908251,"score_gpt":0.2396192334495905,"score_spread":0.220618604580508,"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."}}