{"id":"W4415745066","doi":"10.1016/j.cemconcomp.2025.106387","title":"Multifactorial analysis of AAR development: Integrating laboratory and field data with statistical and probabilistic modelling","year":2025,"lang":"en","type":"article","venue":"Cement and Concrete Composites","topic":"Concrete and Cement Materials Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Reliability (semiconductor); Bayesian probability; Cementitious; Aggregate (composite); Durability; Statistical inference; Alkali–aggregate reaction; Field (mathematics); Bayesian inference","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":[0.0001547405,0.0001157038,0.0002481652,0.0001333892,0.00006856087,0.00007856161,0.00008724783,0.00003508334,0.00002853561],"category_scores_gemma":[0.00002350719,0.00009657144,0.000006219136,0.0001745928,0.00006213009,0.00008199257,0.0001498227,0.00006908894,1.511744e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001118474,"about_ca_system_score_gemma":0.00002656645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005013842,"about_ca_topic_score_gemma":0.00002732994,"domain_scores_codex":[0.9993252,0.00002067235,0.0002134818,0.0002060365,0.0001020833,0.0001325652],"domain_scores_gemma":[0.9994346,0.0002875174,0.00002288085,0.0001566643,0.00005089233,0.00004738927],"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":[0.001368753,0.00003005904,0.1312576,0.005055751,0.01078261,0.00002818126,0.005353625,0.008944779,0.7606429,0.02414524,0.0004557364,0.05193477],"study_design_scores_gemma":[0.0006810437,0.00009946593,0.0007737672,0.000149046,0.0005373755,2.258908e-7,0.0002007068,0.9716583,0.02459965,0.00003127692,0.001067414,0.000201731],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9565365,0.0008219313,0.04217677,0.00001206495,0.00003828046,0.0001541747,0.00007032175,0.00002472053,0.0001651842],"genre_scores_gemma":[0.9940167,0.000236628,0.005542147,0.00001323024,0.00001398053,0.000009637992,0.0001542492,0.000005995028,0.000007415801],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9627135,"threshold_uncertainty_score":0.3938069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0196303145117192,"score_gpt":0.2581510173151755,"score_spread":0.2385207028034563,"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."}}