{"id":"W4210751309","doi":"10.1016/j.engstruct.2022.113913","title":"Design and experimental investigation of deep beams based on the Generative Tie Method","year":2022,"lang":"en","type":"article","venue":"Engineering Structures","topic":"Structural Behavior of Reinforced Concrete","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Truss; Finite element method; Structural engineering; Computer science; Compression (physics); Digital image correlation; Design methods; Generative grammar; Engineering; Artificial intelligence; Mechanical engineering; Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001110819,0.0001675922,0.0001345414,0.00009113394,0.00009396621,0.00001885988,0.000143116,0.0000330722,0.0001243091],"category_scores_gemma":[0.00001816718,0.0001365266,0.00003405698,0.0001339631,0.00002820501,0.00004440338,0.00003543234,0.0002183429,2.401941e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007407329,"about_ca_system_score_gemma":0.000009002725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004724249,"about_ca_topic_score_gemma":9.493285e-9,"domain_scores_codex":[0.9993281,0.0000499529,0.0001435875,0.0001253557,0.0002116377,0.0001413846],"domain_scores_gemma":[0.9995549,0.0001934651,0.0000301432,0.0001691436,0.00001067906,0.00004163752],"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":[0.000006330205,8.607574e-8,0.000005139707,0.000007448156,0.00001361302,0.000001173569,0.0004754913,0.8344161,0.1635203,0.001033925,0.00003380537,0.0004865964],"study_design_scores_gemma":[0.0001047488,0.00004349014,0.0002832911,0.000002470178,0.000007100522,0.000005496564,0.00006344162,0.5326803,0.466603,0.00007902621,0.00003646252,0.00009114452],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4885598,0.0003178559,0.5102224,0.00004098678,0.0003341211,0.0002997966,0.000009267048,0.0001767957,0.0000389449],"genre_scores_gemma":[0.8564188,6.069336e-7,0.1433808,0.00006434369,0.00002800815,0.00006721329,0.000007685018,0.00002911665,0.000003352256],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.367859,"threshold_uncertainty_score":0.5567394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01303045964692583,"score_gpt":0.2285692233698607,"score_spread":0.2155387637229349,"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."}}