{"id":"W2585249400","doi":"","title":"Evaluating A Priori Ozone Profile Information Used in TEMPO Tropospheric Ozone Retrievals","year":2016,"lang":"en","type":"article","venue":"NASA STI Repository (National Aeronautics and Space Administration)","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Environmental science; Troposphere; Air quality index; Tropospheric ozone; Meteorology; Satellite; Lidar; Remote sensing; Tropopause; Ozone; Ozone Monitoring Instrument; Observatory; SCIAMACHY; Temporal resolution; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.0004672382,0.0002125639,0.0001847337,0.00001711956,0.0002376129,0.00008100007,0.000132625,0.0001360502,0.0003417364],"category_scores_gemma":[0.0001574398,0.0001734401,0.00004239304,0.0002379264,0.00024635,0.0009104097,0.0001035881,0.0001283987,0.00008888415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006543508,"about_ca_system_score_gemma":0.0001202187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005170034,"about_ca_topic_score_gemma":0.00004341721,"domain_scores_codex":[0.9978578,0.00008084084,0.0005336349,0.0003303775,0.0009319984,0.0002653558],"domain_scores_gemma":[0.9992415,0.0001389833,0.0002748184,0.0001726798,0.00003428162,0.0001377512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004774121,0.000582971,0.9003333,0.00005835795,0.00005878132,0.00002698421,0.0008225414,0.01317197,0.05700113,0.008141401,0.000519876,0.01880528],"study_design_scores_gemma":[0.001975622,0.0007448645,0.9625968,0.00005378223,0.00002685251,0.00007323788,0.0002192806,0.02809785,0.001046082,0.001050371,0.003650257,0.0004649747],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9822837,0.0000279318,0.01091375,0.001216219,0.000137503,0.000445655,0.00001077775,0.00004113592,0.00492334],"genre_scores_gemma":[0.9722424,0.00002896026,0.02432882,0.0001136684,0.00005050223,0.00004559774,0.00002364438,0.00001445778,0.00315198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06226352,"threshold_uncertainty_score":0.7072682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01490672329071731,"score_gpt":0.2638342773257963,"score_spread":0.248927554035079,"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."}}