{"id":"W3041549652","doi":"10.3390/min10070611","title":"Valorization of Kimberlite Tailings by Carbon Capture and Utilization (CCU) Method","year":2020,"lang":"en","type":"article","venue":"Minerals","topic":"Concrete and Cement Materials Research","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Kimberlite; Tailings; Carbonation; Cement; Cementitious; Environmental science; Compressive strength; Portland cement; Waste management; Materials science; Pulp and paper industry; Metallurgy; Geology; Geochemistry; Composite material; Engineering","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":[0.00008779646,0.00006939877,0.0001228723,0.00002442403,0.00000950899,0.0000179293,0.00004040549,0.00004572283,0.00008609269],"category_scores_gemma":[0.00003160855,0.00006768048,0.00001308245,0.0001188996,0.000008698701,0.00005045667,0.00001834215,0.00003744303,0.000001404023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006742956,"about_ca_system_score_gemma":0.000004091015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008909639,"about_ca_topic_score_gemma":0.00000261364,"domain_scores_codex":[0.9995342,0.00002867491,0.0001397178,0.00009729954,0.000104465,0.0000956206],"domain_scores_gemma":[0.9998254,0.00001834451,0.00001794126,0.00005748223,0.00003260651,0.00004825769],"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":[0.000006357344,0.000001415067,0.000145578,0.0001328068,0.0000111203,4.46949e-7,0.0005243839,0.0003865726,0.9962947,0.00004810303,0.001654246,0.0007942622],"study_design_scores_gemma":[0.0002767438,0.00003784275,0.00004316887,0.0000152847,0.0000157415,5.457065e-7,0.00005726057,0.1432137,0.8433051,0.00003855379,0.01289759,0.00009850277],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881306,0.0008106339,0.008446913,0.0002204348,0.00005365288,0.0001333681,0.00001938309,0.00006806843,0.002116968],"genre_scores_gemma":[0.9988347,0.0001780765,0.0005570562,0.00006033091,0.00005229808,0.00000632549,0.00006758551,0.00001480616,0.0002288211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1529896,"threshold_uncertainty_score":0.275993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02999529053278081,"score_gpt":0.272107457656685,"score_spread":0.2421121671239042,"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."}}