{"id":"W2968230458","doi":"10.5194/acp-19-10087-2019","title":"Clear-sky ultraviolet radiation modelling using output from the Chemistry Climate Model Initiative","year":2019,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Atmospheric Ozone and Climate","field":"Earth and Planetary Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Scheme for Promotion of Academic and Research Collaboration; Université de Lille; Université de La Réunion; Natural Environment Research Council; Centre National d’Etudes Spatiales; Centre National de la Recherche Scientifique; Sight Research UK","keywords":"Northern Hemisphere; Atmospheric sciences; Southern Hemisphere; Environmental science; Ozone; Climatology; Ozone Monitoring Instrument; Latitude; Representative Concentration Pathways; Climate model; Tropospheric ozone; Climate change; Troposphere; Meteorology; Geography; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001134255,0.0002554265,0.0002489892,5.213152e-8,0.0002628973,0.0001008528,0.0002090466,0.0001290402,0.001681773],"category_scores_gemma":[0.000005774433,0.0002035659,0.00008461867,0.0001505427,0.00009496803,0.0002698564,0.00002355608,0.0002769023,0.00008980789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001241552,"about_ca_system_score_gemma":0.00006716595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006152911,"about_ca_topic_score_gemma":0.00000270811,"domain_scores_codex":[0.9987372,0.00002439588,0.0002414723,0.0004059355,0.0002220274,0.0003690118],"domain_scores_gemma":[0.9992335,0.0001562471,0.0001577836,0.0003088237,0.00003741279,0.000106165],"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":[0.00008453279,0.0000247466,0.04642829,0.00007184924,0.00005674494,0.000002646241,0.0007661447,0.8793558,0.001547676,0.000008358336,0.00005091269,0.07160229],"study_design_scores_gemma":[0.0003340454,0.00001225275,0.002675697,0.00003803143,0.00005637401,0.000003979353,0.000606627,0.9930338,0.001451052,0.001150509,0.0003484329,0.0002891532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980354,0.0005997759,0.008479937,0.00004185474,0.00005556809,0.0001200879,0.0001693707,0.00004728907,0.01013214],"genre_scores_gemma":[0.9891683,0.0006314573,0.008801359,0.0003224388,0.0003215128,0.000001461136,0.0003050785,0.00001406836,0.0004343484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.113678,"threshold_uncertainty_score":0.9992308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01803441391970258,"score_gpt":0.2068177133511944,"score_spread":0.1887832994314918,"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."}}