{"id":"W4380203509","doi":"10.1007/978-3-031-33211-1_17","title":"Development of an Experimental-Numerical Approach to Model Cement Paste Microstructure Using Quantitative Phase Assemblage from XRD and Thermodynamic Modeling","year":2023,"lang":"en","type":"book-chapter","venue":"Rilem bookseries","topic":"Concrete and Cement Materials Research","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Microstructure; Microscale chemistry; Materials science; Portland cement; Multiscale modeling; Phase (matter); Porosity; Cement; Thermodynamics; Composite material; Chemistry; Physics; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001182313,0.0004905325,0.0006061797,0.000183406,0.0001258817,0.0001090806,0.0002155009,0.0002045558,0.00005333208],"category_scores_gemma":[0.000002558728,0.0004952278,0.00007005106,0.00003112182,0.00005766018,0.000161481,0.0002627368,0.0001922412,0.000007992117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001757229,"about_ca_system_score_gemma":0.00009617777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000279265,"about_ca_topic_score_gemma":0.00001292524,"domain_scores_codex":[0.9981788,0.0000182248,0.0005695504,0.000495222,0.0004004322,0.0003378081],"domain_scores_gemma":[0.9993582,0.00001978369,0.00008209738,0.000319997,0.00005888244,0.0001609764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001872715,0.0000183033,1.890714e-7,0.0002064009,0.0002438849,0.000005965228,0.00587714,0.09040391,0.8981159,0.004124562,0.000009529968,0.0008069397],"study_design_scores_gemma":[0.0004426461,0.00009740544,5.82657e-7,0.0001903838,0.00004297316,0.000001373959,0.0009539204,0.9484293,0.04825703,0.0009001559,0.0001613314,0.0005228621],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.902985,0.0003472713,0.08881079,0.000002099388,0.0001313518,0.0006520308,0.0004794215,0.0001661109,0.00642588],"genre_scores_gemma":[0.8983383,0.00006836543,0.09734535,0.00001820947,0.00009064426,0.00009187058,0.0006664296,0.0003130561,0.003067827],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8580254,"threshold_uncertainty_score":0.99975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08745756765558396,"score_gpt":0.3143355469236642,"score_spread":0.2268779792680802,"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."}}