{"id":"W4319337761","doi":"10.1016/j.envres.2023.115446","title":"Source apportionment of PM2.5 using organic/inorganic markers and emission inventory evaluation in the East Mediterranean-Middle East city of Beirut","year":2023,"lang":"en","type":"article","venue":"Environmental Research","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"Horizon 2020; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Norges Forskningsråd","keywords":"Middle East; Environmental science; Apportionment; Emission inventory; Mediterranean climate; Air quality index; Physical geography; Geography; Meteorology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0002475962,0.000289773,0.0003204464,0.001116266,0.0003520892,0.0006108799,0.0003299425,0.0003058078,0.0006185049],"category_scores_gemma":[0.0002469316,0.0001814439,0.0003123703,0.000957996,0.0001659479,0.0002200916,0.0003558501,0.0001253908,0.0002029809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001005503,"about_ca_system_score_gemma":0.0005309036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1669783,"about_ca_topic_score_gemma":0.1962812,"domain_scores_codex":[0.9997944,0.00004033698,0.00002276213,0.00005052862,0.00004096414,0.00005091579],"domain_scores_gemma":[0.9999027,0.00001439965,0.00001914231,0.000005928355,0.00004618569,0.00001163207],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002562427,0.00009984225,0.9677838,0.00007496918,0.0001548695,0.0009045326,0.001574993,0.002103902,0.007569146,0.0001159576,0.0005031331,0.01885849],"study_design_scores_gemma":[0.000004189045,0.0000291769,0.9955314,0.00000933193,0.00004356597,0.00009540616,0.001203718,0.001927856,0.0006908583,0.00002047064,0.0004379907,0.000006043972],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988147,0.00009988574,0.0002242167,0.00001958442,0.00000391089,0.000008884024,0.0003629703,0.000008099704,0.0004577463],"genre_scores_gemma":[0.9987564,0.00007145212,0.0003283179,0.00001063292,0.000004931428,0.00001071958,0.0003867909,0.000004823186,0.0004260208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1669783,"threshold_uncertainty_score":0.3320128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2970827775280463,"score_gpt":0.3956210275360311,"score_spread":0.09853825000798483,"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."}}