{"id":"W4407195507","doi":"10.2139/ssrn.5127047","title":"Machine Learning Approaches for Rcpt Modeling of Concrete","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Artificial intelligence; Machine learning","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","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0009463785,0.0003103848,0.0004779201,0.0002066357,0.0001154702,0.00004072274,0.0003646796,0.0002737012,0.000002324681],"category_scores_gemma":[0.00006341725,0.0002980941,0.000295374,0.00007411491,0.00001962987,0.00006148993,0.0001207444,0.004860769,4.172319e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007373239,"about_ca_system_score_gemma":0.0008977677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000372759,"about_ca_topic_score_gemma":0.00004009677,"domain_scores_codex":[0.997523,0.00003083426,0.0004757263,0.0002133345,0.0001634923,0.001593691],"domain_scores_gemma":[0.9994572,0.00004251555,0.0001546174,0.0001861124,0.0001148855,0.00004465308],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003183401,0.000001273775,0.00009284905,0.000334174,0.0004438504,4.897025e-7,0.0001971211,0.9650424,0.0001250913,0.01529323,0.00001150947,0.01842619],"study_design_scores_gemma":[0.0004074287,0.00006126141,0.000002309857,0.0002636238,0.0001199708,0.00003352137,0.0005658242,0.9137777,0.0004290557,0.08352365,0.0005499946,0.0002656531],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03066589,0.01873378,0.945918,0.00005134908,0.001630072,0.0003493621,0.0000271166,0.000148817,0.002475594],"genre_scores_gemma":[0.9890583,0.006853126,0.002716283,0.00000574007,0.000709404,0.00002944034,0.00003249571,0.00005578774,0.0005394351],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9583924,"threshold_uncertainty_score":0.9999471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01522760295186681,"score_gpt":0.2243915700372313,"score_spread":0.2091639670853645,"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."}}