{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00107586,0.0004844927,0.0003505916,0.0004970147,0.0002255266,0.0007770083,0.0004954722,0.0005361358,0.0008534307],"category_scores_gemma":[0.004483785,0.0002011986,0.0003625381,0.0003580977,0.0001139351,0.000971745,0.0005893874,0.0003895108,0.0002465798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003267322,"about_ca_system_score_gemma":0.0005346011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006229092,"about_ca_topic_score_gemma":0.0059664,"domain_scores_codex":[0.999724,0.00005213993,0.00002161308,0.00004054641,0.0001175023,0.00004420735],"domain_scores_gemma":[0.9992686,0.0003205289,0.00007932352,0.00007256872,0.0002207705,0.00003820006],"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":[0.001319434,0.000407137,0.04552405,0.0001624069,0.0002615151,0.0001542151,0.00008100487,0.6579763,0.09015293,0.0009729689,0.001535606,0.2014524],"study_design_scores_gemma":[0.00004981037,0.0001285146,0.01391629,0.000006774769,0.00002509759,0.00002575888,0.0000397329,0.9723573,0.01282882,0.0001598619,0.0004468114,0.00001527909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8808716,0.0004012975,0.1137916,0.0001607136,0.00006163353,0.0001152507,0.001285174,0.001045197,0.002267563],"genre_scores_gemma":[0.9219734,0.000163592,0.0734491,0.00005832017,0.00002694758,0.00004232832,0.003534623,0.00009823568,0.0006535151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006229092,"threshold_uncertainty_score":0.01238567,"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."}}