{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006593585,0.0007345774,0.0003269098,0.0009291065,0.0009370923,0.002136495,0.000956806,0.001322248,0.0131769],"category_scores_gemma":[0.001515871,0.0002933717,0.0003901219,0.0007131535,0.0006071308,0.001722524,0.001043532,0.0007818022,0.00194986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001677133,"about_ca_system_score_gemma":0.002452625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006258365,"about_ca_topic_score_gemma":0.01397491,"domain_scores_codex":[0.9992207,0.0001188131,0.00001796284,0.0001161701,0.0004572706,0.00006905812],"domain_scores_gemma":[0.9996473,0.00007043645,0.00002317241,0.00006623345,0.0001761505,0.00001677599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002288165,0.0003173539,0.005206306,0.001285633,0.0000787125,0.0006420992,0.0004031216,0.1035967,0.05003951,0.1945409,0.01467188,0.6289889],"study_design_scores_gemma":[0.0001576314,0.001467227,0.01117948,0.0004976062,0.0001614217,0.001828003,0.002782408,0.2580312,0.09596759,0.1687174,0.4590601,0.0001498874],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.1017183,0.005395805,0.536366,0.007501209,0.000356443,0.000987903,0.0005600164,0.0009966468,0.3461177],"genre_scores_gemma":[0.7341494,0.004434501,0.2098935,0.0005155242,0.00008867277,0.0003190374,0.000329779,0.0001567794,0.05011294],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.0131769,"threshold_uncertainty_score":0.04408109,"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."}}