{"id":"W2013685991","doi":"10.1016/j.egypro.2009.01.026","title":"CO2 capture for refineries, a practical approach","year":2009,"lang":"en","type":"article","venue":"Energy Procedia","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Shell (Canada)","funders":"","keywords":"Refinery; Oil refinery; Carbon capture and storage (timeline); Combustion; Waste management; Process engineering; Environmental science; Stack (abstract data type); Environmental economics; Engineering; Computer science; Chemistry; Economics","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":[0.00006308273,0.0001933332,0.0002034519,0.00006344697,0.00001739858,0.00003073162,0.0001533353,0.0002587252,0.000005633015],"category_scores_gemma":[0.0002613699,0.0001789848,0.0000666675,0.00021548,0.00003932398,0.0001181659,0.0000183206,0.0001918015,0.000002686897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006969639,"about_ca_system_score_gemma":0.00003602658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005537056,"about_ca_topic_score_gemma":0.00001032215,"domain_scores_codex":[0.9991677,0.000004169436,0.0001596651,0.0002230393,0.0001281816,0.000317175],"domain_scores_gemma":[0.9995458,0.00004876854,0.00002608026,0.0002668966,0.00004961086,0.00006283275],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008908202,0.0001204914,0.00003917424,0.0001617267,0.00009073649,0.0000315734,0.0003302565,0.008871181,0.01843868,0.6004416,0.3517742,0.01961132],"study_design_scores_gemma":[0.00095951,0.0001585231,0.000302565,0.00002640568,0.00006499823,0.0002180407,0.0003741618,0.03389745,0.03370173,0.01513721,0.9142563,0.0009030415],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0615158,0.01414122,0.5168532,0.009769836,0.002046018,0.001443602,0.0001070916,0.02584847,0.3682747],"genre_scores_gemma":[0.9534214,0.00006684232,0.04490584,0.0003684706,0.0002386227,0.0001548088,0.00004419079,0.00004220243,0.0007576207],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8919056,"threshold_uncertainty_score":0.7298788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01191947567884786,"score_gpt":0.2207700994107366,"score_spread":0.2088506237318888,"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."}}