{"id":"W2018007850","doi":"10.1016/j.cemconcomp.2014.09.017","title":"Probabilistic numerical modelling of cracking in steel fibre reinforced concretes (SFRC) structures","year":2014,"lang":"en","type":"article","venue":"Cement and Concrete Composites","topic":"Numerical methods in engineering","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Cracking; Materials science; Probabilistic logic; Ultimate tensile strength; Composite material; Bridging (networking); Structural engineering; Beam (structure); Computer simulation; Shear (geology); Computer science; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007647229,0.0004748547,0.0005953069,0.0006430761,0.0005583086,0.0008422181,0.001297131,0.001937169,0.001170432],"category_scores_gemma":[0.003129437,0.0008009535,0.0005658069,0.0005136814,0.001567095,0.000861262,0.0007625296,0.0006392617,0.0001513447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007910505,"about_ca_system_score_gemma":0.000706304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01278105,"about_ca_topic_score_gemma":0.01123192,"domain_scores_codex":[0.9995635,0.0001327076,0.00002197173,0.0000579782,0.0001760839,0.00004774891],"domain_scores_gemma":[0.9987432,0.0007436737,0.0002287341,0.0000801691,0.000156577,0.0000476677],"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":[0.000007820265,0.000007252683,0.0002284906,0.00001118222,0.000003099484,0.00001653792,0.00001496031,0.9962409,0.0008387871,0.001774668,0.00002356083,0.0008328262],"study_design_scores_gemma":[0.000001172941,0.000003694132,0.000143504,0.000001459351,0.000001152721,0.000006331876,0.000002584918,0.9992912,0.0001572657,0.0003476269,0.00004221059,0.000001859843],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5769233,0.0007473299,0.408564,0.0003910756,0.0000631166,0.00006912291,0.000159971,0.000312807,0.0127693],"genre_scores_gemma":[0.9856238,0.0001529028,0.01229084,0.00001182274,0.00001217358,0.00002214216,0.00003800005,0.00003072871,0.001817486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01278105,"threshold_uncertainty_score":0.02541333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01764763584448424,"score_gpt":0.2247852518085848,"score_spread":0.2071376159641005,"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."}}