{"id":"W4229714245","doi":"10.5194/acp-2020-1117","title":"Measurement report: Regional trends of stratospheric ozoneevaluated using the MErged GRIdded Dataset of Ozone Profiles(MEGRIDOP)","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Canadian Space Agency; Jet Propulsion Laboratory; Universität Bremen; Deutsches Zentrum für Luft- und Raumfahrt; Academy of Finland; Deutscher Akademischer Austauschdienst; European Space Agency; Freie Hansestadt Bremen; California Institute of Technology; National Aeronautics and Space Administration","keywords":"Stratosphere; Polar vortex; SCIAMACHY; Environmental science; Ozone; Latitude; Northern Hemisphere; Climatology; Atmospheric sciences; Ozone Monitoring Instrument; Satellite; Longitude; Ozone layer; Meteorology; Troposphere; Geography; Geology; Geodesy; Physics","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":[0.001146236,0.0006368628,0.0003793759,0.0009256935,0.000237592,0.0006672283,0.0006989704,0.0004157656,0.001661014],"category_scores_gemma":[0.00147408,0.00020785,0.0005630289,0.001685953,0.000113221,0.0007170625,0.0009332729,0.0005026955,0.0009428521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004398094,"about_ca_system_score_gemma":0.0007062087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02755741,"about_ca_topic_score_gemma":0.02775843,"domain_scores_codex":[0.9993727,0.00009324161,0.00006401097,0.0001903459,0.0002110092,0.00006879737],"domain_scores_gemma":[0.9989132,0.0000726638,0.0002477015,0.0002716604,0.000386507,0.0001083091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008571919,0.0005088533,0.6946899,0.001129209,0.001892351,0.0003817815,0.0004357541,0.01459894,0.01096116,0.001356198,0.2072793,0.06590944],"study_design_scores_gemma":[0.0001922584,0.0001769886,0.8877263,0.00008467575,0.0002651474,0.0001388074,0.0002997057,0.01322625,0.006626486,0.0003733185,0.09082945,0.00006052427],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.2077722,0.0003421031,0.003611494,0.0002597519,0.000123777,0.0001737195,0.7845915,0.000941748,0.002183814],"genre_scores_gemma":[0.146885,0.0001356856,0.006129358,0.00005734752,0.00003450603,0.0002319963,0.8455499,0.0001090876,0.0008670717],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02755741,"threshold_uncertainty_score":0.05479401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1227573299676039,"score_gpt":0.2951589027188427,"score_spread":0.1724015727512388,"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."}}