{"id":"W2403878665","doi":"10.1002/ente.201600024","title":"Combined Calcium Looping and Chemical Looping Combustion for Post‐Combustion Carbon Dioxide Capture: Process Simulation and Sensitivity Analysis","year":2016,"lang":"en","type":"article","venue":"Energy Technology","topic":"Chemical Looping and Thermochemical Processes","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; University of Ottawa","funders":"Engineering and Physical Sciences Research Council; Carbon Management Canada","keywords":"Calcium looping; Chemical looping combustion; Combustion; Carbon dioxide; Carbon capture and storage (timeline); Sensitivity (control systems); Work (physics); Process engineering; Calcium oxide; Chemistry; Materials science; Process (computing); Oxide; Thermodynamics; Chemical engineering; Nuclear engineering; Computer science; Engineering; Metallurgy; Physical chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008647181,0.0002059481,0.0003382099,0.0002358153,0.00005627292,0.00001425818,0.00005602511,0.0003896103,0.000001569215],"category_scores_gemma":[0.0002907486,0.0001766535,0.00004752623,0.0004993547,0.0001578989,0.00008286753,0.0000490357,0.0001266817,1.760845e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006879147,"about_ca_system_score_gemma":0.000009374688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003220317,"about_ca_topic_score_gemma":0.000009964628,"domain_scores_codex":[0.9990376,0.00001318114,0.000228414,0.0003524722,0.00008874064,0.0002796372],"domain_scores_gemma":[0.9993157,0.0002664065,0.00005848065,0.0001661278,0.0001258311,0.00006749998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006310241,0.00002660637,0.001401853,0.0002164607,0.0002088214,0.000003443942,0.00003400625,0.01418429,0.9716728,0.001739622,0.000002959995,0.01044604],"study_design_scores_gemma":[0.00069448,0.0000297558,0.000170393,0.0001120899,0.0001955935,0.000009981518,0.00002798651,0.1831645,0.8106467,0.004628253,0.00002487228,0.0002954291],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8685067,0.0003666319,0.1299044,0.000499832,0.00004572299,0.0000769516,0.000007051665,0.0005605692,0.00003214592],"genre_scores_gemma":[0.9995006,0.00003615641,0.0002827705,0.00003280191,0.0000466667,0.00003150223,0.00002674051,0.00002964731,0.00001316479],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1689802,"threshold_uncertainty_score":0.7203721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007386524955164333,"score_gpt":0.2279096532857876,"score_spread":0.2205231283306232,"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."}}