{"id":"W4310731191","doi":"10.5194/acp-2022-743","title":"OMI UV aerosol index data analysis over the Arctic region for future data assimilation and climate forcing applications","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Aeronautics and Space Administration","keywords":"Aerosol; Ozone Monitoring Instrument; Environmental science; Arctic; Climatology; Atmospheric sciences; Air quality index; Latitude; Meteorology; Oceanography; Geography; Geology","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":[0.001290588,0.0005800715,0.0004212331,0.001100046,0.000608679,0.0008046121,0.0005900239,0.0003883809,0.001494743],"category_scores_gemma":[0.001470676,0.000229986,0.0008052296,0.001781897,0.00008525979,0.0005400175,0.0004376199,0.0004850781,0.0007145747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007129214,"about_ca_system_score_gemma":0.001840498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07789095,"about_ca_topic_score_gemma":0.09805761,"domain_scores_codex":[0.999719,0.00005605877,0.00002728464,0.00006004485,0.00011093,0.00002671861],"domain_scores_gemma":[0.9993256,0.00003981469,0.00007607442,0.0001209492,0.0003980108,0.0000394981],"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":[0.0006087858,0.0007715545,0.3822537,0.0006584698,0.001717508,0.0003370478,0.0004336232,0.183104,0.06863162,0.00420061,0.07432477,0.2829581],"study_design_scores_gemma":[0.00015306,0.00009890688,0.343289,0.0001565439,0.0002658938,0.0000630956,0.0002656799,0.5683099,0.0265124,0.001657874,0.05911513,0.0001123946],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6798402,0.001490097,0.1143309,0.001060881,0.0009658114,0.0005553879,0.1758577,0.01226306,0.01363601],"genre_scores_gemma":[0.759756,0.0004317639,0.1516646,0.0001637816,0.0001481469,0.0003998509,0.08442074,0.0006737643,0.002341281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07789095,"threshold_uncertainty_score":0.1548751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05105175357599212,"score_gpt":0.2845913269895264,"score_spread":0.2335395734135343,"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."}}