{"id":"W6976518246","doi":"10.60692/43rgy-40d43","title":"Global Surface Ozone Concentration Dataset 1990-2017 Generated by Bayesian Maximum Entropy Data Fusion With RAMP Bias Correction","year":2023,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bayesian probability; Ozone; Metric (unit); Tropospheric ozone; Sensor fusion; Principle of maximum entropy; Entropy (arrow of time); Fusion","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":[0.0007325002,0.0007152655,0.0007613574,0.001269551,0.0002751752,0.0005240613,0.000945875,0.0006657667,0.002932891],"category_scores_gemma":[0.002068213,0.0002399471,0.001002371,0.002216834,0.0002192871,0.0005269267,0.0009024041,0.0008644377,0.003327295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007402061,"about_ca_system_score_gemma":0.001326148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05888952,"about_ca_topic_score_gemma":0.06016311,"domain_scores_codex":[0.9995303,0.00007457333,0.00004001845,0.0001371582,0.0001605355,0.00005741143],"domain_scores_gemma":[0.9992029,0.00007400058,0.00007069614,0.0001639761,0.0004542705,0.00003413781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007276469,0.0004437441,0.08532907,0.001219932,0.0009430973,0.0003396902,0.0001543089,0.06529398,0.00699909,0.002743862,0.7699412,0.06586448],"study_design_scores_gemma":[0.0008742159,0.0002935025,0.3632509,0.0004365557,0.000446605,0.0002771344,0.0003760745,0.1074168,0.01165446,0.005189192,0.5095832,0.0002013659],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.03488642,0.0002322169,0.002797494,0.0002380411,0.0001140645,0.00009035333,0.958679,0.000884344,0.002077984],"genre_scores_gemma":[0.02361829,0.0000602402,0.002251021,0.00003577353,0.00002081949,0.00008383759,0.973437,0.00004635279,0.0004467259],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05888952,"threshold_uncertainty_score":0.1170934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06730796081818653,"score_gpt":0.2504369877130089,"score_spread":0.1831290268948224,"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."}}