{"id":"W4406119690","doi":"10.1021/acs.iecr.4c03772","title":"Binary CO<sub>2</sub>/H<sub>2</sub>O Adsorption on CO<sub>2</sub> Capture Metal–Organic Frameworks CALF-20, Al-Fumarate and CAU-10-H Using Microscale Dynamic Column Breakthrough","year":2025,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Total; Mitacs; Canada Foundation for Innovation","keywords":"Metal-organic framework; Adsorption; Microscale chemistry; Column (typography); Chemistry; Binary number; Materials science; Chromatography; Computer science; Physical chemistry; Mathematics","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":["metaepi_narrow","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.001292974,0.001244228,0.001291822,0.0008532774,0.0002793873,0.0004963565,0.00103721,0.003860152,0.00003009757],"category_scores_gemma":[0.001347012,0.001503489,0.0003450421,0.002710444,0.0006265931,0.0004038267,0.0005949128,0.008281413,0.00006170424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002510564,"about_ca_system_score_gemma":0.0004575894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004377801,"about_ca_topic_score_gemma":0.0000295274,"domain_scores_codex":[0.9937288,0.0001575826,0.001128759,0.001545776,0.00127609,0.00216295],"domain_scores_gemma":[0.9965224,0.0008708176,0.0001756716,0.001566147,0.000378389,0.0004865564],"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":[0.0001858051,0.0001189128,0.00006300289,0.0005257222,0.0003917066,0.0001890599,0.0000847463,0.03644482,0.951804,0.00001617814,0.00849496,0.001681109],"study_design_scores_gemma":[0.001840365,0.0001112659,0.000103671,0.001086328,0.0001329897,0.0001314315,0.0001824357,0.04388613,0.9498479,0.00007575634,0.001424769,0.001176965],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922998,0.002006538,0.0004635476,0.000523985,0.0008778736,0.001240515,0.0003516238,0.001999779,0.0002363521],"genre_scores_gemma":[0.9976019,0.0007463514,0.00007018178,0.00005218728,0.0005074385,0.0002326883,0.0003292972,0.000352629,0.0001073421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007441306,"threshold_uncertainty_score":0.9987414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02347850808861132,"score_gpt":0.2860495417412273,"score_spread":0.262571033652616,"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."}}