{"id":"W3037718612","doi":"10.1186/s40069-020-00406-z","title":"A Simplified Method to Predict Damage of Axially-Loaded Circular RC Columns Under Lateral Impact Loading","year":2020,"lang":"en","type":"article","venue":"International Journal of Concrete Structures and Materials","topic":"Structural Response to Dynamic Loads","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Key Research and Development Program of China; Hunan Provincial Science and Technology Department; National Natural Science Foundation of China","keywords":"Structural engineering; Stiffness; Parametric statistics; Axial symmetry; Deformation (meteorology); Solid mechanics; Finite element method; Hammer; Materials science; Residual; Engineering; Computer science; Composite material; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002434548,0.0002034893,0.0004844762,0.0001567476,0.0000210293,0.000145945,0.0003759887,0.00009500348,0.0005170869],"category_scores_gemma":[0.0001705825,0.0001654676,0.0001248408,0.0000784246,0.00003767705,0.0001906768,0.00008622581,0.0001330398,0.000001410818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008530278,"about_ca_system_score_gemma":0.00007564002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003779896,"about_ca_topic_score_gemma":5.865476e-7,"domain_scores_codex":[0.9985059,0.00009971459,0.0006620075,0.0001343369,0.0004094158,0.0001885694],"domain_scores_gemma":[0.9990815,0.0001262921,0.0002468235,0.00008883359,0.000232649,0.0002238927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006351575,4.138613e-7,0.00007421063,0.00004112389,0.0005211564,0.00005225897,0.0004863551,0.00842586,0.9883184,0.0006620104,0.000227715,0.0005553554],"study_design_scores_gemma":[0.002828574,0.0005186511,0.04313233,0.0001623391,0.0001559301,0.0007540577,0.0001402473,0.004103834,0.9419441,0.004528503,0.001273281,0.0004581762],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866817,0.00008527374,0.01146856,0.0003492222,0.0009190223,0.0001340703,0.0002608793,0.00003121588,0.00007006877],"genre_scores_gemma":[0.9941665,0.00002187664,0.004964156,0.0002887469,0.0005087666,0.000001232062,0.00001078048,0.0000311047,0.000006868707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0463743,"threshold_uncertainty_score":0.6747571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01314020708630586,"score_gpt":0.2894063425357208,"score_spread":0.2762661354494149,"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."}}