{"id":"W4234073552","doi":"10.32920/ryerson.14668638.v1","title":"Parametric study of curved steel I-girder bridges at construction phase.","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Railway Engineering and Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Structural engineering; Girder; Image warping; Curvature; Torsion (gastropod); Engineering; Parametric statistics; Bending moment; Finite element method; Bracing; Computer science; Mathematics; Geometry","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":[0.0001216819,0.0003326828,0.0005590671,0.0003276337,0.00002713603,0.0000541837,0.000189927,0.0002562171,0.0001069131],"category_scores_gemma":[0.00005017034,0.000357906,0.0001316078,0.0003465713,0.00002763794,0.00004734111,0.0002425983,0.0004502155,0.000007336014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001680809,"about_ca_system_score_gemma":0.00002983125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001165037,"about_ca_topic_score_gemma":0.00008684096,"domain_scores_codex":[0.9986295,0.00003379229,0.0004864236,0.0003532425,0.0002721483,0.0002249003],"domain_scores_gemma":[0.9990306,0.00008188702,0.000076104,0.0006252318,0.0001091862,0.00007702807],"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":[0.000006293827,0.0002563787,0.002506843,0.0003812643,0.0003080534,0.00001042991,0.0002445218,0.9921561,0.0004218622,0.00002766081,0.000182249,0.00349831],"study_design_scores_gemma":[0.001578453,0.0001306961,0.008395655,0.0001003015,0.000150472,0.00002233715,0.00146024,0.9854963,0.001871174,0.00001503561,0.0001867013,0.0005926276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9598455,0.0005932857,0.03503277,0.000003573495,0.001896744,0.0003716214,0.00005189328,0.0006098082,0.001594843],"genre_scores_gemma":[0.9953475,0.0002362402,0.003747223,0.000002104898,0.00007239534,0.000037697,0.0001374242,0.0000706062,0.0003488236],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03550202,"threshold_uncertainty_score":0.9998873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01679283126750502,"score_gpt":0.2461559392993166,"score_spread":0.2293631080318116,"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."}}