{"id":"W4220681007","doi":"10.5194/egusphere-egu22-6642","title":"Changes in Aerosols in an Urban Cold Climate During and Before the COVID-19 Outbreak","year":2022,"lang":"en","type":"preprint","venue":"","topic":"COVID-19 impact on air quality","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Université du Québec à Montréal","funders":"","keywords":"Air quality index; Environmental science; Air pollution; Climate change; Particulates; Population; Geography; Pollutant; Coronavirus disease 2019 (COVID-19); Meteorology; Pandemic; Outbreak; Relative humidity; Climatology; Atmospheric sciences; Environmental health; Infectious disease (medical specialty); Disease","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":[0.0003536711,0.0002453334,0.0004031342,0.0005623056,0.001339604,0.001242743,0.0003209928,0.0007198594,0.001222506],"category_scores_gemma":[0.0005730286,0.0001316575,0.0002680204,0.0008051244,0.0004361616,0.0002657763,0.0005017421,0.0005700133,0.0002013057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003893065,"about_ca_system_score_gemma":0.001986678,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5920066,"about_ca_topic_score_gemma":0.7027479,"domain_scores_codex":[0.999814,0.00002586785,0.000007290957,0.00003588098,0.00003770177,0.00007939899],"domain_scores_gemma":[0.9995641,0.00005085103,0.00006395965,0.00002167292,0.0001585908,0.0001407367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007336386,0.0002609961,0.9820322,0.0000475282,0.0001282443,0.0008661681,0.001051833,0.001881096,0.005071935,0.0002010726,0.002528262,0.005196934],"study_design_scores_gemma":[0.00000378039,0.00001714327,0.9987287,0.000002968417,0.000006499541,0.00001450955,0.0003702232,0.0003763573,0.00009279196,0.00001125922,0.0003718477,0.000003929266],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977603,0.00009339121,0.00004845335,0.0001636,0.00002215557,0.00001070252,0.00098175,0.000006484266,0.0009132394],"genre_scores_gemma":[0.9983435,0.00005507978,0.00005658338,0.00005164204,0.00002633207,0.000007924059,0.001132916,0.000003614596,0.0003224219],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5920066,"threshold_uncertainty_score":0.8207923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04669637608497225,"score_gpt":0.3351609239280982,"score_spread":0.288464547843126,"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."}}