{"id":"W2565025435","doi":"10.1021/acs.est.6b04606","title":"Techno–Economic Evaluation of Technologies to Mitigate Greenhouse Gas Emissions at North American Refineries","year":2016,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Carbon Management Canada","keywords":"Greenhouse gas; Oil refinery; Environmental science; Waste management; Refinery; Natural resource economics; Environmental protection; Environmental engineering; Engineering; Economics","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":[0.002427884,0.001080744,0.0008371514,0.00136859,0.0005897985,0.0008515652,0.00117586,0.0008803009,0.001239372],"category_scores_gemma":[0.002920392,0.0007524406,0.001193442,0.001426147,0.0006888135,0.001112173,0.0005952405,0.0008194872,0.0001033069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00604716,"about_ca_system_score_gemma":0.002906844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0633663,"about_ca_topic_score_gemma":0.05435894,"domain_scores_codex":[0.9987481,0.000690567,0.00003440745,0.00008721658,0.0002798876,0.0001597552],"domain_scores_gemma":[0.9984547,0.0009175506,0.0001471609,0.0001058358,0.0003135732,0.00006122307],"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":[0.0002502334,0.0001238475,0.002417868,0.00003761756,0.00004403176,0.00003920593,0.000005843993,0.9935212,0.0008016158,0.0005377894,0.0001167044,0.002104246],"study_design_scores_gemma":[0.0002124427,0.00116484,0.01018404,0.00001553385,0.0001717535,0.00002152553,0.00006241321,0.9821853,0.004318743,0.0007260079,0.0008993739,0.00003804147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886559,0.0002151513,0.003111758,0.0001317886,0.00001023205,0.0001583957,0.0005566595,0.00004655964,0.007113537],"genre_scores_gemma":[0.997428,0.0001545064,0.001390484,0.00002001835,0.000002531411,0.0001018739,0.0002537268,0.000004926691,0.0006439713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0633663,"threshold_uncertainty_score":0.1259949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00783836450953831,"score_gpt":0.2143063652919643,"score_spread":0.206468000782426,"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."}}