{"id":"W3173998642","doi":"10.5194/amt-14-4689-2021","title":"The Adaptable 4A Inversion (5AI): description and first <i>X</i> <sub> CO <sub>2</sub> </sub> retrievals from Orbiting Carbon Observatory-2 (OCO-2) observations","year":2021,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Sorbonne Université; Université de La Réunion; Bundesministerium für Wirtschaft und Energie; Centre National de la Recherche Scientifique; National Aeronautics and Space Administration; Conseil Régional, Île-de-France; California Institute of Technology; European Space Agency; Centre National d’Etudes Spatiales","keywords":"Greenhouse gas; Environmental science; Inversion (geology); Radiative transfer; Observatory; Atmospheric sciences; Meteorology; Physics; Astrophysics; 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":[0.0004358107,0.0004711953,0.0002355651,0.0004922595,0.0002572256,0.0004736315,0.0006699389,0.0005119777,0.001566364],"category_scores_gemma":[0.001029587,0.0002365827,0.0004673824,0.0004454661,0.0002648146,0.0006258469,0.0006733673,0.0005615001,0.0006478804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002490511,"about_ca_system_score_gemma":0.0008736344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005296873,"about_ca_topic_score_gemma":0.005371524,"domain_scores_codex":[0.9998443,0.00003437863,0.00001089248,0.00003576578,0.00005257459,0.00002205189],"domain_scores_gemma":[0.999801,0.00004280679,0.00002312069,0.00004853833,0.00007244947,0.00001215142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004672387,0.0001855093,0.01788789,0.00024046,0.0002003107,0.0003490933,0.0003507969,0.407314,0.1867846,0.013114,0.004714249,0.3683918],"study_design_scores_gemma":[0.00002638139,0.00005813137,0.003442289,0.000009992898,0.00002048832,0.00007613605,0.00004474079,0.9739614,0.01666631,0.001507876,0.004159801,0.00002636399],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1448897,0.0002333239,0.8473262,0.0001920066,0.0001134027,0.0001629091,0.0009021007,0.002183792,0.00399655],"genre_scores_gemma":[0.5239805,0.0001300076,0.4706532,0.000075053,0.00004044973,0.0002263688,0.00204846,0.0002618837,0.002584082],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005296873,"threshold_uncertainty_score":0.01053208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02823581703586947,"score_gpt":0.1960489253483011,"score_spread":0.1678131083124316,"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."}}