{"id":"W7119158462","doi":"10.13016/m2zykd-hgao","title":"Improving data quality in long-term Canadian ozone sounding records","year":2023,"lang":"en","type":"article","venue":"Maryland Shared Open Access Repository (USMAI Consortium)","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Maryland, Baltimore County","keywords":"Depth sounding; Satellite; Ozone; Stratosphere; Ozone depletion; Ozone layer; Atmospheric sounding","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01857436,0.000796763,0.0008844176,0.006715186,0.003647659,0.006775204,0.004768001,0.001121536,0.005367442],"category_scores_gemma":[0.07087476,0.0006547559,0.0007129119,0.01690494,0.0009808583,0.002701108,0.003065015,0.001380591,0.001654505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02113676,"about_ca_system_score_gemma":0.0409301,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9629925,"about_ca_topic_score_gemma":0.9697193,"domain_scores_codex":[0.9833961,0.001447836,0.00181519,0.002247639,0.009428279,0.001664893],"domain_scores_gemma":[0.8891956,0.006728653,0.003938589,0.008629168,0.08948801,0.002019983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008428292,0.0001885573,0.4659029,0.001756835,0.000583764,0.0004090808,0.003392827,0.007444474,0.01743583,0.004483801,0.1358538,0.3617053],"study_design_scores_gemma":[0.0001100623,0.00005496401,0.8354167,0.0008403335,0.0003539538,0.0001129317,0.001973441,0.0113301,0.009033072,0.0009719606,0.1395513,0.0002511884],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5058295,0.008851743,0.03836591,0.0146423,0.001713309,0.001097372,0.3866169,0.003797288,0.03908562],"genre_scores_gemma":[0.6712699,0.003237772,0.06170408,0.001747012,0.0004475714,0.0004606478,0.2482092,0.001028089,0.01189584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03700745,"threshold_uncertainty_score":0.1533586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09961853085291625,"score_gpt":0.3558714383237592,"score_spread":0.2562529074708429,"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."}}