{"id":"W4384028057","doi":"10.1016/j.conbuildmat.2023.132439","title":"Modeling mixing kinetics for large-scale production of Ultra-High-Performance Concrete: effects of temperature, volume, and mixing method","year":2023,"lang":"en","type":"article","venue":"Construction and Building Materials","topic":"Innovative concrete reinforcement materials","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Mixing (physics); Volume (thermodynamics); Torque; Materials science; Kinetics; Thermodynamics; Physics","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":[0.0006309624,0.0001787276,0.000432689,0.0002177896,0.00008555365,0.00004923276,0.00005208204,0.0001162363,0.000009072694],"category_scores_gemma":[0.0001464131,0.0001809245,0.0000219463,0.0002353121,0.00006262587,0.0002016995,0.00003042996,0.00004874748,4.348168e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001851786,"about_ca_system_score_gemma":0.000008767133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004871467,"about_ca_topic_score_gemma":1.186321e-7,"domain_scores_codex":[0.9988809,0.00004527903,0.000526452,0.0002103986,0.0001062847,0.000230743],"domain_scores_gemma":[0.9994763,0.00007094617,0.0001347525,0.0001211108,0.0001676397,0.00002931087],"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":[0.00003478305,8.200474e-7,0.000103043,0.003189138,0.00004419691,1.619522e-7,0.0001639924,0.005651364,0.9888403,0.0008922296,0.00002190829,0.001058012],"study_design_scores_gemma":[0.000558737,0.00006028229,0.0001177066,0.0004722329,0.00004582225,0.00001303136,0.0001141819,0.02661329,0.9716821,0.00008767363,0.00006478341,0.0001701978],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9652417,0.00007818559,0.03176908,0.000009848305,0.00219089,0.0005007282,0.00004567676,0.000150566,0.00001337747],"genre_scores_gemma":[0.9574659,0.0003083994,0.04193229,0.000005594684,0.0001629518,0.00004223814,0.00003362928,0.00003336694,0.00001560864],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02096193,"threshold_uncertainty_score":0.7377885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00851540903463468,"score_gpt":0.2381531136427295,"score_spread":0.2296377046080948,"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."}}