{"id":"W4366420863","doi":"10.3390/atmos14040733","title":"Spatiotemporal Patterns and Characteristics of PM2.5 Pollution in the Yellow River Golden Triangle Demonstration Area","year":2023,"lang":"en","type":"article","venue":"Atmosphere","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Environmental science; Pollution; Seasonality; Spatial ecology; Spatial variability; Physical geography; Structural basin; Drainage basin; Common spatial pattern; Hydrology (agriculture); Atmospheric sciences; Climatology; Geography; Ecology; Geology; Biology; Cartography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000414798,0.00005845408,0.00009655797,0.00000237654,0.00005843559,0.00001080743,0.000073856,0.00005596467,0.0002312681],"category_scores_gemma":[0.00004574083,0.00004473684,0.0000173194,0.0001816798,0.00008873948,0.000131988,0.00003127613,0.0000716148,0.00006785227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003853525,"about_ca_system_score_gemma":0.00001207005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002150778,"about_ca_topic_score_gemma":0.001479732,"domain_scores_codex":[0.9993179,0.00009046261,0.0001903094,0.0001052961,0.0001541862,0.0001418568],"domain_scores_gemma":[0.9997035,0.00005389679,0.00009005867,0.0001109639,0.000003007149,0.00003860332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002192208,0.00003582087,0.9590821,0.00003529945,0.000002611758,0.00000703761,0.003859157,0.0001828359,0.00005972266,0.0001062216,0.004116439,0.03249087],"study_design_scores_gemma":[0.0002123121,0.00006036135,0.9941699,0.00002366131,0.000004348521,0.000001556425,0.0005244984,0.003323414,0.00003699396,0.0003582494,0.001234873,0.00004985694],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950601,0.000008151841,0.0002491621,0.003798314,0.00004006222,0.0001787914,0.00002039832,0.00001430936,0.0006306517],"genre_scores_gemma":[0.9988824,0.00005635692,0.0001972479,0.000646658,0.0000215667,0.000005258902,0.00001916328,0.000004043181,0.0001672637],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03508781,"threshold_uncertainty_score":0.3251348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03581220851079144,"score_gpt":0.271744437854529,"score_spread":0.2359322293437375,"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."}}