{"id":"W4413053562","doi":"10.1016/j.cscm.2025.e05129","title":"Corrigendum to “Predicting residual strength of hybrid fibre-reinforced Self-compacting concrete (HFR-SCC) exposed to elevated temperatures using machine learning” [Case Stud. Constr. Mater. 22 (2025) 1–25 page/e04112]","year":2025,"lang":"en","type":"erratum","venue":"Case Studies in Construction Materials","topic":"Fire effects on concrete materials","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Geomechanica (Canada); University of Manitoba","funders":"","keywords":"Hfr cell; Materials science; Composite material; Residual; Residual strength; Structural engineering; Engineering; Computer science; Algorithm; Chemistry","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":["metaepi_narrow"],"category_scores_codex":[0.002005133,0.001829312,0.003930981,0.001643086,0.0006523169,0.0005098861,0.0005123101,0.0006841703,0.0005376746],"category_scores_gemma":[0.002947578,0.001964523,0.0002411158,0.001089164,0.0004354833,0.0003574104,0.0008934931,0.001312244,0.00002908014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001079948,"about_ca_system_score_gemma":0.0004011412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006108976,"about_ca_topic_score_gemma":0.00004327391,"domain_scores_codex":[0.9916184,0.001252217,0.003527283,0.001434111,0.0007148244,0.001453173],"domain_scores_gemma":[0.9956837,0.0008993965,0.001163221,0.001081809,0.0008033022,0.0003685464],"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":[0.0005787894,0.00001153535,0.0002447865,0.00992455,0.00297059,0.03578107,0.00274164,0.004242533,0.870958,0.0000605527,0.07224304,0.0002428622],"study_design_scores_gemma":[0.002688721,0.0005918846,0.000006534784,0.00716729,0.0009398728,0.02674908,0.008433977,0.005412776,0.9389523,0.000007803476,0.006564774,0.002484977],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9092126,0.001014147,0.0000625324,0.00002690648,0.08121244,0.002748383,0.003890888,0.001299789,0.0005322697],"genre_scores_gemma":[0.9852372,0.000460734,0.007096022,0.00009761137,0.002409825,0.0003113344,0.0007754448,0.0003930773,0.003218687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07880261,"threshold_uncertainty_score":0.9994452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02363180161150737,"score_gpt":0.2799148914591724,"score_spread":0.2562830898476651,"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."}}