{"id":"W2048603472","doi":"10.1021/ef800779k","title":"Long-Term Calcination/Carbonation Cycling and Thermal Pretreatment for CO<sub>2</sub> Capture by Limestone and Dolomite","year":2009,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Chemical Looping and Thermochemical Processes","field":"Engineering","cited_by":163,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Natural Resources Canada","funders":"","keywords":"Carbonation; Calcination; Dolomite; Calcium looping; Carbon dioxide; Thermogravimetric analysis; Chemical engineering; Carbonatation; Calcite; Combustion; Environmental science; Chemistry; Materials science; Mineralogy; Waste management; Pulp and paper industry; Catalysis","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":[0.00003714905,0.0001546387,0.0001491543,0.000028945,0.000050379,0.00003408868,0.00004406331,0.0001190656,0.000002264842],"category_scores_gemma":[0.00001861631,0.0001436121,0.00002892101,0.00005305234,0.00002824147,0.00008383777,0.00000831775,0.00007078364,4.401109e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003880549,"about_ca_system_score_gemma":0.000005289636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005020804,"about_ca_topic_score_gemma":0.000002280065,"domain_scores_codex":[0.9994141,0.000006670317,0.000134323,0.0001916288,0.00008063079,0.0001725834],"domain_scores_gemma":[0.9997105,0.00008342189,0.00002699907,0.00008017571,0.00002564345,0.00007326747],"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":[0.0000131964,0.00002641596,0.0001142345,0.00005306813,0.00002999552,0.000001086962,0.00009340409,0.00009682037,0.967856,0.0001432548,0.00008858008,0.03148397],"study_design_scores_gemma":[0.0004978198,0.00004091564,0.001213313,0.00004409083,0.00002769912,0.000004893019,0.000003910222,0.000743015,0.9965072,0.0006720845,0.00007701712,0.0001680579],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925177,0.005125216,0.001463233,0.0001134718,0.00003876298,0.00007907924,0.00001463471,0.0001425089,0.0005053796],"genre_scores_gemma":[0.999018,0.0004576091,0.0001181708,0.0001035903,0.00009138969,0.00002451272,0.0001097273,0.00002119495,0.00005584681],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03131592,"threshold_uncertainty_score":0.5856332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005695621059682458,"score_gpt":0.2161393183946142,"score_spread":0.2104436973349317,"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."}}