{"id":"W4250714909","doi":"10.5194/amt-2017-236","title":"Tomographic retrievals of ozone with the OMPS Limb Profiler: algorithm description and preliminary results","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Stratosphere; Remote sensing; Microwave Limb Sounder; Altitude (triangle); Environmental science; Ozone; Ozone layer; Polar vortex; Satellite; Atmospheric sciences; Meteorology; Algorithm; Physics; Geology; Mathematics; Geometry; Astronomy","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":[0.000800794,0.0007117321,0.0004122753,0.0005608617,0.0003406941,0.0009054767,0.000901418,0.0007121036,0.00335736],"category_scores_gemma":[0.00268025,0.0003725379,0.0003598027,0.001005515,0.0001641626,0.0006943439,0.0006064799,0.0005197377,0.001999668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004960459,"about_ca_system_score_gemma":0.0008982157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01484217,"about_ca_topic_score_gemma":0.01313254,"domain_scores_codex":[0.9996511,0.0000586217,0.00002528569,0.00006394922,0.0001737359,0.00002734121],"domain_scores_gemma":[0.9995539,0.0001312143,0.00002781612,0.00008390926,0.0001864869,0.00001670801],"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":[0.0009093077,0.001010237,0.02786854,0.0004276343,0.0004089249,0.0002351658,0.0001492389,0.3106624,0.07704166,0.002622538,0.01818667,0.5604777],"study_design_scores_gemma":[0.0002013444,0.0001079136,0.007394088,0.00001063646,0.00002397864,0.00006517193,0.00003487607,0.9696257,0.0182345,0.0006269395,0.003639445,0.00003553994],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2469447,0.000709712,0.7145956,0.0004710289,0.0000959706,0.00134035,0.0143751,0.01590512,0.005562373],"genre_scores_gemma":[0.2295092,0.0002247353,0.7457646,0.00008253474,0.00002242715,0.0009220821,0.0209517,0.0005287119,0.001994029],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01484217,"threshold_uncertainty_score":0.02951151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02214047397988633,"score_gpt":0.224040594939167,"score_spread":0.2019001209592807,"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."}}