{"id":"W2755590865","doi":"10.3390/environments4030066","title":"Air Quality Impacts of Petroleum Refining and Petrochemical Industries","year":2017,"lang":"en","type":"article","venue":"Environments","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":127,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Oil refinery; Petrochemical; Air quality index; Pollutant; Environmental science; Refining (metallurgy); Industrialisation; Waste management; Natural resource economics; Quality (philosophy); Greenhouse gas; Air pollution; Particulates; Environmental engineering; Environmental protection; Business; Environmental planning; Engineering; Geography; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000579722,0.0001391219,0.0002293636,0.0000152966,0.0003875308,0.00002195816,0.0002743018,0.0001275294,0.0005208814],"category_scores_gemma":[0.00036497,0.0001307479,0.00002983086,0.00002011967,0.0007197026,0.0003632469,0.0004616982,0.0002116156,0.0001369922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001209609,"about_ca_system_score_gemma":0.00001114144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008540787,"about_ca_topic_score_gemma":0.00004583965,"domain_scores_codex":[0.9986375,0.00006936233,0.0003128953,0.0002729117,0.0003710184,0.0003363109],"domain_scores_gemma":[0.9987629,0.00006175594,0.0003561945,0.0005465117,9.153971e-7,0.000271721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005043719,0.00008994107,0.9759803,0.0000239757,0.00001084949,0.000002606241,0.0004351704,0.00001937923,0.01412283,0.00008856857,0.001327655,0.007848327],"study_design_scores_gemma":[0.000468403,0.000085638,0.9697631,0.00002189568,0.000008098148,0.000002694998,0.00009544528,0.00002347311,0.01085744,0.0001776627,0.01836134,0.0001348239],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903921,0.00003789871,0.0000668681,0.001650667,0.0000474541,0.00005309789,0.00001528081,0.000009998748,0.007726656],"genre_scores_gemma":[0.9976479,0.00005838288,0.0006780538,0.0005473669,0.00003030328,0.000004021084,0.000004668667,0.0000108055,0.001018443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01703368,"threshold_uncertainty_score":0.5703285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05547052888226706,"score_gpt":0.3343834911674106,"score_spread":0.2789129622851435,"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."}}