{"id":"W2025237931","doi":"10.1007/s00376-009-9103-6","title":"Temporal variability in fine carbonaceous aerosol over two years in two megacities: Beijing and Toronto","year":2010,"lang":"en","type":"article","venue":"Advances in Atmospheric Sciences","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Beijing; Aerosol; Megacity; Seasonality; Environmental science; Atmospheric sciences; Climatology; Air pollutants; Meteorology; Air pollution; Geography; Physical geography; China; Chemistry; Geology; Biology; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0001621316,0.0002328562,0.0002563164,0.001139637,0.0008018616,0.000727947,0.0005065773,0.0003626613,0.001060937],"category_scores_gemma":[0.0005658816,0.0001988586,0.0002530618,0.002643445,0.0003282123,0.000359331,0.0007753462,0.0002311584,0.0001585423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005692481,"about_ca_system_score_gemma":0.002022503,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8853843,"about_ca_topic_score_gemma":0.9431432,"domain_scores_codex":[0.9998606,0.00001415396,0.00001157282,0.00003703985,0.00002995993,0.00004667194],"domain_scores_gemma":[0.9993464,0.00006905337,0.0001539917,0.00003564122,0.0002325718,0.0001623074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001242431,0.00001818255,0.9934852,0.00002124476,0.00008492453,0.0002588046,0.001532128,0.0004735138,0.001044518,0.00010119,0.0006666744,0.002189362],"study_design_scores_gemma":[0.000001201676,0.000003591787,0.9990208,0.000001171419,0.000009033763,0.00001319502,0.0005334519,0.0001978684,0.00004923576,0.000002599492,0.0001653906,0.000002546555],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983144,0.00008973614,0.00002985928,0.00004811262,0.000002109295,0.000003638364,0.00113035,0.000004625196,0.0003771582],"genre_scores_gemma":[0.9986445,0.00006217493,0.00003411606,0.000006805803,0.000002911573,0.00000445149,0.0008266103,0.000001359709,0.0004171806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1146157,"threshold_uncertainty_score":0.2305813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006531909243943671,"score_gpt":0.2661340896228634,"score_spread":0.2596021803789197,"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."}}