{"id":"W4385602360","doi":"10.1007/978-3-031-34159-5_70","title":"Machine Learning Driven Shear Strength Prediction Model for FRP-Reinforced Concrete Beams","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Concrete Corrosion and Durability","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia; Lakehead University; Polytechnique Montréal; University of Alberta","funders":"","keywords":"Fibre-reinforced plastic; Reinforced concrete; Structural engineering; Shear (geology); Shear strength (soil); Beam (structure); Reinforcement; Materials science; Computer science; Engineering; Composite material; Geology","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":[],"category_scores_codex":[0.0002352008,0.0007073942,0.0007195699,0.0004137946,0.00007351374,0.00005765407,0.0002519137,0.000811594,0.0001176116],"category_scores_gemma":[0.0004623633,0.0007910264,0.0003073309,0.0001227181,0.00003098389,0.000110267,0.00009263564,0.001556113,0.00002288622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003340894,"about_ca_system_score_gemma":0.00004330184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000122595,"about_ca_topic_score_gemma":0.00008543048,"domain_scores_codex":[0.9979178,0.000008008411,0.0006540616,0.0005435247,0.000310297,0.0005663472],"domain_scores_gemma":[0.9985968,0.0006496255,0.00008049976,0.0004441957,0.00007020978,0.0001587094],"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":[0.00001964967,3.523244e-7,0.00001210524,0.0005098998,0.00005299869,0.000005729034,0.0003014674,0.9943057,0.00179286,0.001027787,0.00004740584,0.001923997],"study_design_scores_gemma":[0.000568291,0.00006136584,0.000006021877,0.0005054379,0.00005729066,0.000004521597,0.00000145203,0.9912912,0.0005176276,0.0004544,0.005871609,0.000660765],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003666793,0.000887846,0.9869388,0.00004116154,0.001324437,0.0009537505,0.000470766,0.002837777,0.006178733],"genre_scores_gemma":[0.9575743,0.001561684,0.01220218,0.00009342287,0.001232224,0.0003799833,0.00227368,0.001423169,0.02325932],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9747367,"threshold_uncertainty_score":0.9994541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0125916191824566,"score_gpt":0.2023925505764587,"score_spread":0.1898009313940021,"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."}}