{"id":"W4409799952","doi":"10.11159/iceptp25.152","title":"Correlation Between Temperature Inversions and PM Concentrations: A Seasonal and Diurnal Perspective in Turin, Italy","year":2025,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Civil, Structural, and Environmental Engineering","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Perspective (graphical); Environmental science; Atmospheric sciences; Climatology; Diurnal temperature variation; Geology; Computer science","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":[0.0003109409,0.0002641615,0.0002271038,0.000630744,0.0001551117,0.0005086564,0.0003348546,0.0003109337,0.001284507],"category_scores_gemma":[0.0005725073,0.000125313,0.0002328377,0.0007307805,0.0003655972,0.000150853,0.0003739651,0.0002060801,0.00032214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004475865,"about_ca_system_score_gemma":0.0001815641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01992903,"about_ca_topic_score_gemma":0.02266401,"domain_scores_codex":[0.9998139,0.00006283198,0.00001157664,0.00005539322,0.00001470703,0.0000417244],"domain_scores_gemma":[0.9995659,0.00009093566,0.0001767335,0.00004132759,0.00004883812,0.00007623144],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003093792,0.00007100889,0.9897139,0.00005611017,0.00009746289,0.0003145481,0.0006409578,0.0003809155,0.001235863,0.0000402603,0.00135181,0.005787692],"study_design_scores_gemma":[0.000001446546,0.0000203965,0.9995775,0.000002929684,0.000005310813,0.0000333225,0.00006430913,0.00013738,0.00001792923,0.000003219847,0.0001350026,0.000001237183],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981257,0.0004361207,0.00007581848,0.00007346855,0.00001116822,0.000006113781,0.0006810442,0.00002035396,0.0005701659],"genre_scores_gemma":[0.9992869,0.00008957865,0.00005871317,0.00001511467,0.00001485167,0.000005600155,0.0003834064,0.000005776601,0.0001401279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01992903,"threshold_uncertainty_score":0.03962606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005322368521922361,"score_gpt":0.2066542252411734,"score_spread":0.201331856719251,"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."}}