{"id":"W4211213179","doi":"10.5194/acpd-11-4263-2011","title":"Inverse modeling of CO <sub>2</sub> sources and sinks using satellite observations of CO <sub>2</sub> from TES and surface flask measurements","year":2011,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Environment and Climate Change Canada","funders":"Natural Sciences and Engineering Research Council of Canada; California Institute of Technology; Jet Propulsion Laboratory; University of Toronto; National Aeronautics and Space Administration","keywords":"Biomass burning; Environmental science; Atmospheric sciences; Troposphere; Inversion (geology); Latitude; Southern Hemisphere; Climatology; Meteorology; Chemistry; Aerosol; Geology; Geodesy; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003112202,0.0005152654,0.0002778728,0.0003155009,0.0002137312,0.0005560502,0.0004691627,0.0004067371,0.0003627066],"category_scores_gemma":[0.0006847196,0.0004622567,0.0006757991,0.0003629854,0.0003589097,0.0006470982,0.0003913055,0.0004695173,0.0001168985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007802221,"about_ca_system_score_gemma":0.001090476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03955464,"about_ca_topic_score_gemma":0.0327121,"domain_scores_codex":[0.9999162,0.00001344255,0.000004386404,0.00002446514,0.00002588454,0.00001564552],"domain_scores_gemma":[0.9998418,0.00006004782,0.00002679398,0.00001912299,0.00003706728,0.00001505647],"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":[0.0001898085,0.00008602777,0.04313793,0.00003848831,0.0001638559,0.00009654032,0.00007550672,0.9047416,0.03335927,0.001478461,0.0002939753,0.01633839],"study_design_scores_gemma":[0.00001088489,0.000009326905,0.007513326,0.000001538673,0.00001725927,0.000006202792,0.0000110662,0.9888909,0.00311364,0.0002653244,0.0001507079,0.000009909491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9729903,0.00006411305,0.02507297,0.00009326063,0.00001213948,0.00001190845,0.0002244836,0.0001454016,0.001385387],"genre_scores_gemma":[0.9926375,0.00003199782,0.006749074,0.00001227287,0.000004886756,0.000008190148,0.00025493,0.00002451945,0.000276597],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03955464,"threshold_uncertainty_score":0.07864881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06209336637479451,"score_gpt":0.2287566391758921,"score_spread":0.1666632728010976,"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."}}