{"id":"W2519997812","doi":"10.1016/j.cemconcomp.2016.09.005","title":"Predicting the flexural behavior of ultra-high-performance fiber-reinforced concrete","year":2016,"lang":"en","type":"article","venue":"Cement and Concrete Composites","topic":"Innovative concrete reinforcement materials","field":"Engineering","cited_by":112,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Ministry of Education, Science and Technology; National Research Foundation of Korea","keywords":"Materials science; Bridging (networking); Fiber; Fiber-reinforced concrete; Flexural strength; Softening; Ultimate tensile strength; Cracking; Composite material; Orientation (vector space); Micromechanics; Structural engineering; Mathematics; Geometry; Computer science","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":[0.0002302567,0.0007329453,0.0002080038,0.0004585196,0.0002245075,0.0002888512,0.0004385562,0.0008932851,0.0006093851],"category_scores_gemma":[0.0005843045,0.0003541115,0.0002633372,0.0002504147,0.0002447104,0.0004644629,0.0002021938,0.0003365749,0.0001807327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004933834,"about_ca_system_score_gemma":0.0004226519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01076011,"about_ca_topic_score_gemma":0.01620277,"domain_scores_codex":[0.999922,0.00001117166,0.000003891728,0.00002166479,0.00002531091,0.00001590352],"domain_scores_gemma":[0.9997204,0.0001382073,0.00004550677,0.00001996512,0.00004463088,0.00003137403],"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":[0.000110419,0.000138461,0.01653356,0.00002548617,0.00001859187,0.00009925821,0.00001854325,0.9323487,0.03981142,0.0001815993,0.00007766111,0.01063631],"study_design_scores_gemma":[0.000002277241,0.00003006114,0.004476008,9.070849e-7,0.000003407343,0.000008600849,0.000006313506,0.9870206,0.008372373,0.00004092138,0.00003453979,0.000003988788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924504,0.00003899017,0.006857578,0.00001035389,0.000003427764,0.00000698494,0.00005124246,0.0001085403,0.0004725273],"genre_scores_gemma":[0.9977869,0.00001953761,0.001796694,0.000001496186,0.000001220912,0.000002676541,0.00005637242,0.000006362701,0.000328738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01076011,"threshold_uncertainty_score":0.02139491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01080587648833638,"score_gpt":0.208332872600248,"score_spread":0.1975269961119117,"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."}}