{"id":"W3159390225","doi":"10.5194/acp-21-6663-2021","title":"Linking global terrestrial CO <sub>2</sub> fluxes and environmental drivers: inferences from the Orbiting Carbon Observatory 2 satellite and terrestrial biospheric models","year":2021,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Nuclear Safety and Security Commission; National Oceanic and Atmospheric Administration; Agence Nationale de la Recherche; National Aeronautics and Space Administration","keywords":"Biome; Biosphere; Environmental science; Precipitation; Atmospheric sciences; Carbon cycle; Satellite; Climatology; Observatory; Terrestrial ecosystem; Representative Concentration Pathways; Climate change; Ecosystem; Meteorology; Geography; Climate model; Ecology; Biology; Physics; Geology","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":[0.001600872,0.0004993555,0.0001782864,0.0006301713,0.000202103,0.0008949234,0.0003075316,0.0003242274,0.0006059362],"category_scores_gemma":[0.004110939,0.0002423271,0.0007121864,0.001026612,0.0002866895,0.0009165495,0.0006965386,0.0003924615,0.000133251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005917351,"about_ca_system_score_gemma":0.0005705998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02760944,"about_ca_topic_score_gemma":0.0259963,"domain_scores_codex":[0.9996934,0.0001160729,0.00002313569,0.00009151253,0.0000453648,0.00003055255],"domain_scores_gemma":[0.9987522,0.0005444767,0.0003111176,0.0001467597,0.0001545818,0.00009087516],"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":[0.00009028445,0.0000469905,0.9441127,0.00005033596,0.0004450972,0.00006057205,0.00007046391,0.04418308,0.002333667,0.0008131679,0.0008993084,0.006894366],"study_design_scores_gemma":[0.00003553096,0.0000401705,0.7933919,0.00003164836,0.0002046525,0.00003274823,0.0002729278,0.2009685,0.001438293,0.00178992,0.001766161,0.00002746712],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964613,0.0001678439,0.001092321,0.0002883141,0.000008482036,0.000006115653,0.0009770565,0.00004212865,0.0009564836],"genre_scores_gemma":[0.9978956,0.00007886328,0.0007009263,0.00004146436,0.000008812071,0.000005245244,0.001177419,0.00001481062,0.00007681661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02760944,"threshold_uncertainty_score":0.05489749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009721422539797958,"score_gpt":0.1902440800029989,"score_spread":0.180522657463201,"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."}}