{"id":"W2038400370","doi":"10.1029/2006jd007463","title":"Quantifying Arctic ozone loss during the 2004–2005 winter using satellite observations and a chemical transport model","year":2007,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Environment and Climate Change Canada; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Jet Propulsion Laboratory; Canadian Space Agency; Canadian Foundation for Climate and Atmospheric Sciences; California Institute of Technology; National Aeronautics and Space Administration","keywords":"Arctic; Occultation; Microwave Limb Sounder; Environmental science; Chemical transport model; Atmospheric sciences; Satellite; Ozone depletion; Climatology; Stratosphere; Meteorology; Geology; Physics; Troposphere; Oceanography; Astrophysics","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":[0.0003611059,0.0007102746,0.0002838027,0.0005375361,0.0004996951,0.0005915626,0.000458368,0.0004856137,0.0002863551],"category_scores_gemma":[0.0003374522,0.0003496554,0.0008501379,0.0005519376,0.0001626274,0.0004693426,0.0002969744,0.0003366951,0.00009018127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001843471,"about_ca_system_score_gemma":0.0007099521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.14409,"about_ca_topic_score_gemma":0.1106312,"domain_scores_codex":[0.9998939,0.00001575249,0.00000884358,0.00003391128,0.00002710565,0.00002059697],"domain_scores_gemma":[0.9998711,0.00002084465,0.0000339384,0.0000206613,0.00003823009,0.00001509772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000623561,0.0002397967,0.399208,0.00008360605,0.0005290368,0.000193681,0.0001577382,0.5597544,0.02617524,0.0005122911,0.0009395622,0.01158309],"study_design_scores_gemma":[0.0000654125,0.0001511535,0.3065411,0.00001431061,0.0001792731,0.00005384279,0.0000956144,0.6828017,0.008748666,0.0002075997,0.001104923,0.0000363837],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958574,0.00007766506,0.002015492,0.00004344201,0.000006938953,0.000009944028,0.0009428727,0.000132627,0.0009136007],"genre_scores_gemma":[0.9953099,0.00006753105,0.002461682,0.00002016609,0.000006416499,0.00001146213,0.001855926,0.00001696053,0.0002500057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.14409,"threshold_uncertainty_score":0.2865026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08549787361744378,"score_gpt":0.3256026701258745,"score_spread":0.2401047965084307,"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."}}