{"id":"W2781631477","doi":"10.5194/amt-11-3433-2018","title":"A study of the approaches used to retrieve aerosol extinction, as applied to limb observations made by OSIRIS and SCIAMACHY","year":2018,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Canadian Space Agency; Universität Bremen; Deutsches Zentrum für Luft- und Raumfahrt; Centre National d’Etudes Spatiales; Deutscher Akademischer Austauschdienst; Tekes; Bundesministerium für Bildung und Forschung; European Space Agency; Freie Hansestadt Bremen","keywords":"SCIAMACHY; Radiative transfer; Aerosol; Remote sensing; Normalization (sociology); Environmental science; A priori and a posteriori; Extinction (optical mineralogy); Satellite; Meteorology; Range (aeronautics); Atmospheric radiative transfer codes; Inversion (geology); Stratosphere; Atmospheric sciences; Physics; Geography; Geology; Optics; Troposphere","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":[0.003417849,0.0003925468,0.0002758222,0.0006972622,0.000380409,0.0006821374,0.0003820946,0.0005350472,0.0002681475],"category_scores_gemma":[0.006128977,0.0002140477,0.0003429744,0.001318402,0.0002456485,0.0006517768,0.0003529667,0.0003002091,0.0001431267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007610132,"about_ca_system_score_gemma":0.0004078827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0101322,"about_ca_topic_score_gemma":0.0137448,"domain_scores_codex":[0.999161,0.0002967932,0.00004104718,0.0001460173,0.0003047552,0.00005031725],"domain_scores_gemma":[0.9976478,0.00134933,0.0003096954,0.0001696622,0.0004943951,0.00002916012],"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":[0.0008055454,0.0004556674,0.383561,0.0006938781,0.0009068857,0.0003028702,0.001060893,0.2450056,0.1233613,0.003216126,0.0008459541,0.2397843],"study_design_scores_gemma":[0.0001083627,0.001071212,0.5211074,0.0001114892,0.0003243239,0.0003444885,0.0005223283,0.3824937,0.08637096,0.0009829375,0.006458033,0.0001049023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984132,0.0007116821,0.0129608,0.00006260906,0.00001876623,0.00005911121,0.0003187608,0.00005737216,0.001678969],"genre_scores_gemma":[0.9735745,0.0005587012,0.02488622,0.00002427966,0.000008120747,0.000039975,0.0004802868,0.00003481641,0.0003930793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0101322,"threshold_uncertainty_score":0.02014643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08682470168010926,"score_gpt":0.2435265799759159,"score_spread":0.1567018782958066,"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."}}