{"id":"W4367400357","doi":"10.1016/j.istruc.2023.04.069","title":"Machine learning models for predicting concrete beams shear strength externally bonded with FRP","year":2023,"lang":"en","type":"article","venue":"Structures","topic":"Structural Behavior of Reinforced Concrete","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fibre-reinforced plastic; Random forest; Reinforced concrete; Shear (geology); Beam (structure); Structural engineering; Computer science; Range (aeronautics); Materials science; Composite material; Machine learning; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001035929,0.0009038765,0.0006577448,0.0006640213,0.000351312,0.0005940163,0.0009491077,0.001285695,0.001341456],"category_scores_gemma":[0.003144018,0.0004337962,0.0006424816,0.0005343497,0.0004007289,0.0006666098,0.0003934195,0.001277712,0.0004438435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008485476,"about_ca_system_score_gemma":0.0005417425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01375824,"about_ca_topic_score_gemma":0.01140131,"domain_scores_codex":[0.9997647,0.0000719782,0.00001462125,0.0000659877,0.00004505639,0.00003756077],"domain_scores_gemma":[0.9979619,0.001496346,0.0001615282,0.00006734314,0.0002724511,0.00004041955],"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":[0.00002540282,0.00004921785,0.001117472,0.0000096219,0.00001532987,0.00001211005,0.000006438828,0.9830246,0.0003712275,0.0002990204,0.0002673391,0.01480219],"study_design_scores_gemma":[6.361515e-7,0.000003353589,0.0001072767,7.608873e-7,0.000001034776,8.57588e-7,6.774194e-7,0.999671,0.00006662209,0.0001336627,0.00001350723,6.473389e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5839322,0.001410419,0.4091245,0.0005977425,0.0001359427,0.00006460568,0.0007161233,0.001062965,0.00295549],"genre_scores_gemma":[0.9785774,0.0001930154,0.01825579,0.00004605724,0.00004489988,0.00006161763,0.0004263268,0.00002818539,0.002366747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01375824,"threshold_uncertainty_score":0.02735633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01443750850966261,"score_gpt":0.2285099664697686,"score_spread":0.214072457960106,"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."}}