{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001097276,0.0005159071,0.0004109181,0.000002638792,0.00113631,0.0002036438,0.0004171901,0.0002860762,0.00006498426],"category_scores_gemma":[0.0002456696,0.0004699906,0.0001437711,0.0006190903,0.0003748572,0.0006051958,0.000505877,0.0004250961,0.00004009378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001452045,"about_ca_system_score_gemma":0.00006899073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001144299,"about_ca_topic_score_gemma":0.0008973202,"domain_scores_codex":[0.9959643,0.0002478223,0.0007002198,0.0009358398,0.00143273,0.0007190478],"domain_scores_gemma":[0.9983086,0.0001631321,0.0003868031,0.0008065677,0.00007206825,0.0002628571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004364322,0.000155461,0.09960563,0.00002345835,0.00006234257,0.00002255168,0.0001918114,0.001041465,0.8692197,0.00003882228,0.00453421,0.02506095],"study_design_scores_gemma":[0.0005327495,0.0002228776,0.07638273,0.000266644,0.0001864284,0.00001518904,0.0008332104,0.02443514,0.873661,0.001498025,0.02101094,0.0009550586],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812288,0.001254949,0.01409067,0.0006699417,0.0002289549,0.000796961,0.000008442498,0.0004005394,0.001320713],"genre_scores_gemma":[0.9611307,0.006054102,0.03144316,0.0008321449,0.00009854502,0.0002094035,0.00005002956,0.00009503871,0.00008686875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02410589,"threshold_uncertainty_score":0.9997752,"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."}}