{"id":"W4402993686","doi":"10.1016/j.istruc.2024.107378","title":"Parametric optimization of SIP connection geometry in CFS-MRF structures: A finite element study","year":2024,"lang":"en","type":"article","venue":"Structures","topic":"Structural Load-Bearing Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de recherche du Québec","keywords":"Connection (principal bundle); Finite element method; Parametric statistics; Structural engineering; Geometry; Materials science; Computer science; Acoustics; Physics; Engineering; Mathematics","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":[0.0005091708,0.0005143459,0.0004447692,0.0007094192,0.0002606197,0.0004779039,0.0005878102,0.001142333,0.001777561],"category_scores_gemma":[0.001096374,0.0003120554,0.0005117974,0.0004039894,0.0004338661,0.0002783107,0.0003914717,0.0002804435,0.0002027417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003818885,"about_ca_system_score_gemma":0.0004940216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002528236,"about_ca_topic_score_gemma":0.00269159,"domain_scores_codex":[0.9998331,0.00004693918,0.000006231418,0.00002277874,0.00005408977,0.00003683368],"domain_scores_gemma":[0.9996645,0.0001793526,0.00006385696,0.00002807892,0.00004361483,0.0000204895],"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":[0.00003207418,0.00003900496,0.001187384,0.00004284543,0.000008264476,0.00008571355,0.00003358345,0.988501,0.003479445,0.0007946899,0.0001367822,0.005659283],"study_design_scores_gemma":[0.00000454775,0.00007095544,0.0005724808,0.000008341594,0.000006552827,0.00003147722,0.00003624543,0.9976764,0.0009720927,0.0001347322,0.0004807813,0.000005283589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8137916,0.0003473306,0.1686217,0.0001598871,0.00002852057,0.0001452008,0.0002909753,0.0001576544,0.01645713],"genre_scores_gemma":[0.968509,0.0001260442,0.02969516,0.00001189249,0.000005358046,0.00008604046,0.0001047873,0.00002376019,0.001438024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002528236,"threshold_uncertainty_score":0.005946517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009418456250362115,"score_gpt":0.246420264325019,"score_spread":0.2370018080746569,"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."}}