{"id":"W4391786693","doi":"10.28924/2291-8639-22-2024-30","title":"Application of Deep Belief Network in Weather Modeling: PM2.5 Concentration in Thailand","year":2024,"lang":"en","type":"article","venue":"International Journal of Analysis and Applications","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Kementerian Sumber Asli dan Alam Sekitar; Prince of Songkla University","keywords":"Deep belief network; Mathematics; Meteorology; Artificial intelligence; Computer science; Artificial neural network; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047986,0.0005573095,0.0003242441,0.0004469367,0.0003276111,0.0007066726,0.0005839365,0.0006923579,0.0005840923],"category_scores_gemma":[0.001554442,0.0003253815,0.0004706119,0.0005140566,0.0002846444,0.0007096501,0.0004525203,0.0008414845,0.00008396248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008904897,"about_ca_system_score_gemma":0.0008096436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.078339,"about_ca_topic_score_gemma":0.03132519,"domain_scores_codex":[0.999843,0.00004840913,0.00001026856,0.00004387185,0.00002506828,0.00002938151],"domain_scores_gemma":[0.9994862,0.0002956461,0.00005359208,0.00001630938,0.0001175059,0.00003068783],"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":[0.00003232612,0.00002532565,0.006140776,0.00001195822,0.00001920757,0.0000393403,0.00002253782,0.9872765,0.0002294269,0.0001783986,0.0001143047,0.005909921],"study_design_scores_gemma":[9.40591e-7,0.000002919839,0.0004084265,7.108124e-7,0.000001315977,0.000001505198,0.000005812051,0.9994044,0.00006415039,0.00009565365,0.0000129084,0.000001244207],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8682113,0.0003908297,0.1277151,0.0006182972,0.00004924925,0.0000296927,0.0004807077,0.000296512,0.00220824],"genre_scores_gemma":[0.9934037,0.0000950688,0.005660165,0.00001995219,0.00000838646,0.00001147555,0.0001979508,0.000006683891,0.0005965201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.078339,"threshold_uncertainty_score":0.155766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01129599956407596,"score_gpt":0.2794384933222917,"score_spread":0.2681424937582157,"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."}}