{"id":"W2329202517","doi":"10.1021/acs.iecr.6b00469","title":"CO<sub>2</sub> Capture Performance of Core/Shell CaO-Based Sorbent Using Mesostructured Silica and Titania in a Multicycle CO<sub>2</sub> Capture Process","year":2016,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Chemical Looping and Thermochemical Processes","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Calcination; Sorbent; Materials science; Mesoporous material; Chemical engineering; Sintering; Pellets; Porosity; Scanning electron microscope; Physisorption; Mesoporous silica; Mineralogy; Adsorption; Composite material; Chemistry; Catalysis; Organic 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001281478,0.0004100212,0.0002522947,0.0001882304,0.0001365251,0.0002088925,0.0002423014,0.0003809357,0.0006097546],"category_scores_gemma":[0.0001710244,0.0002017228,0.0002818067,0.0001490031,0.0002212908,0.0002588387,0.0002094695,0.000215177,0.0002545694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002744366,"about_ca_system_score_gemma":0.0002013686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001027705,"about_ca_topic_score_gemma":0.003310404,"domain_scores_codex":[0.9999034,0.000006179569,0.000007103218,0.00002484087,0.00003628535,0.00002214452],"domain_scores_gemma":[0.9999126,0.00001592068,0.0000211056,0.000006854019,0.00002664162,0.00001684333],"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":[0.00003480554,0.000007397923,0.000132728,0.00002953981,0.000004596722,0.00002297,0.000008721972,0.0001153356,0.9989856,0.00001075972,0.00001397724,0.0006335468],"study_design_scores_gemma":[0.000004742618,0.0001419201,0.001916171,0.000001596515,0.00001002712,0.00005746265,0.00001507826,0.001347972,0.9962177,0.000005656317,0.000276768,0.000004868666],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982716,0.0001895653,0.0009442439,0.00001575168,0.000009407968,0.00001376609,0.00006509066,0.00003198897,0.0004585106],"genre_scores_gemma":[0.9961396,0.0002300141,0.002425477,0.00002323085,0.000004017134,0.00001311806,0.00009621034,0.00001559248,0.001052825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001027705,"threshold_uncertainty_score":0.002043426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03856732035472432,"score_gpt":0.2868372747618502,"score_spread":0.2482699544071258,"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."}}