{"id":"W2061595583","doi":"10.1021/ie900703d","title":"CO<sub>2</sub>Sequestration in Concrete through Accelerated Carbonation Curing in a Flow-through Reactor","year":2009,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Concrete and Cement Materials Research","field":"Engineering","cited_by":163,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies; Concordia University","keywords":"Carbonation; Carbon dioxide; Dissolution; Curing (chemistry); Materials science; Volumetric flow rate; Carbonate; Cement; Carbonatation; Environmental science; Carbon sequestration; Chemical engineering; Waste management; Pulp and paper industry; Chemistry; Composite material; Metallurgy; Thermodynamics; 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":[0.0002324083,0.0004864237,0.0003318941,0.0001906555,0.0002339727,0.0003265323,0.0002487537,0.0002944755,0.000532879],"category_scores_gemma":[0.0002018215,0.0002070698,0.0002686611,0.0001191922,0.0004285944,0.0003871722,0.000159628,0.0003803963,0.0001773838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003869383,"about_ca_system_score_gemma":0.0005129612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002593159,"about_ca_topic_score_gemma":0.003282638,"domain_scores_codex":[0.9999138,0.00001485001,0.000004509919,0.00002048443,0.00002648072,0.00001989523],"domain_scores_gemma":[0.9998617,0.00002875347,0.0000484225,0.00001272329,0.00002251074,0.00002591637],"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":[0.00008488374,0.00002761407,0.0002492836,0.00003213544,0.000004381961,0.00004285009,0.00001981844,0.001021879,0.9971426,0.00006828547,0.00001596508,0.001290238],"study_design_scores_gemma":[0.0000161248,0.0002377579,0.001473027,0.000003753527,0.00001678801,0.00006538173,0.000009592055,0.004928194,0.9928262,0.00002604881,0.0003867407,0.0000103429],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945571,0.0002368993,0.004595885,0.0000305924,0.000009295818,0.00001870686,0.00004017254,0.0001296417,0.0003817482],"genre_scores_gemma":[0.9942215,0.0002455986,0.004572871,0.00000901597,0.000004899458,0.00001083668,0.00004178105,0.00002304031,0.000870568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002593159,"threshold_uncertainty_score":0.005156159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0991780996685381,"score_gpt":0.3362963615939616,"score_spread":0.2371182619254235,"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."}}