{"id":"W2802301219","doi":"10.20944/preprints201804.0257.v1","title":"Trace Gas Retrieval from AIUS：Algorithm Description and O&lt;sub&gt;3&lt;/sub&gt; Retrieval Assessment","year":2018,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Canadian Space Agency; National Natural Science Foundation of China","keywords":"Stratosphere; Trace gas; Troposphere; Remote sensing; Occultation; A priori and a posteriori; Atmospheric chemistry; Spectral line; Environmental science; Meteorology; Ozone; Physics; Geology; Astrophysics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006906823,0.001147428,0.000548098,0.0006316298,0.0005976856,0.001169189,0.001619235,0.0007085975,0.008128356],"category_scores_gemma":[0.001570361,0.0002960412,0.0005979369,0.0006633126,0.0002421541,0.0007464034,0.0009796433,0.0008744639,0.004823957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007723703,"about_ca_system_score_gemma":0.001514478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01140377,"about_ca_topic_score_gemma":0.006791087,"domain_scores_codex":[0.9996268,0.00005275092,0.00003274342,0.00007540462,0.0001610459,0.00005134],"domain_scores_gemma":[0.9996368,0.00005932442,0.00002375151,0.00004457701,0.0002161566,0.00001946084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006148471,0.0002256616,0.003699988,0.0002419803,0.0001846272,0.0001578892,0.0001126275,0.2221933,0.03284592,0.005368424,0.01756606,0.7167886],"study_design_scores_gemma":[0.00008048623,0.0000436803,0.0006067701,0.000009050998,0.00001411472,0.00004125554,0.00002415895,0.9851155,0.008521779,0.001062574,0.00446421,0.00001652022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01882531,0.0002599342,0.9662101,0.0001355257,0.00006063826,0.0004948894,0.0006086784,0.01034131,0.003063546],"genre_scores_gemma":[0.1288988,0.0002963812,0.8545536,0.0002189159,0.00006843231,0.001636726,0.005319417,0.0006964463,0.008311129],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01140377,"threshold_uncertainty_score":0.027192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05863938279769474,"score_gpt":0.2882078441856477,"score_spread":0.2295684613879529,"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."}}