{"id":"W3176580744","doi":"10.1155/2021/6680564","title":"Characteristics and Meteorological Factors of Severe Haze Pollution in China","year":2021,"lang":"en","type":"article","venue":"Advances in Meteorology","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Oceanic and Atmospheric Administration; Shenzhen Fundamental Research Program; Wuhan University; China Scholarship Council","keywords":"Haze; Environmental science; Relative humidity; Pollution; Air quality index; Air pollution; Wind speed; Atmospheric sciences; Mass concentration (chemistry); Pollutant; Climatology; Meteorology; Geography; Physical geography; Chemistry; Geology; Biology","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":[0.0004192533,0.00009800311,0.0003019584,0.00004240655,0.00003134135,0.000002847521,0.00008543774,0.0001334904,0.0004947647],"category_scores_gemma":[0.0004998576,0.00008640478,0.00001965329,0.0002267068,0.0002782887,0.0002345739,0.000119129,0.0001991507,0.000006966161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006715824,"about_ca_system_score_gemma":0.00001556915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001722186,"about_ca_topic_score_gemma":0.001436122,"domain_scores_codex":[0.9987358,0.0002913405,0.0003303741,0.0002496917,0.0001056869,0.0002871386],"domain_scores_gemma":[0.9995524,0.0001383813,0.0001081353,0.0001278814,0.000004079748,0.00006916495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000746025,0.00009739981,0.9732766,0.00003387134,0.00000220302,0.00002631956,0.0006410878,0.000508824,0.0008966984,0.001749108,0.00002694687,0.02266635],"study_design_scores_gemma":[0.0003005796,0.0001712268,0.9831178,0.000007815907,0.000003720519,0.00001607819,0.00008018618,0.000183042,0.0004206441,0.008568879,0.007045283,0.00008477457],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958623,0.0007671493,0.0002273516,0.001743887,0.000113257,0.00008187476,0.00001293089,0.0000077369,0.001183509],"genre_scores_gemma":[0.9943252,0.001584432,0.002776317,0.001246211,0.000009848127,0.000004443672,0.000008705996,0.000004204467,0.00004061588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02258158,"threshold_uncertainty_score":0.5417326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01888976857102362,"score_gpt":0.3013615348546883,"score_spread":0.2824717662836647,"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."}}