{"id":"W2083061379","doi":"10.1007/s001580100104","title":"On buckling optimization under uncertain loading combinations","year":2001,"lang":"en","type":"article","venue":"Structural and Multidisciplinary Optimization","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute for Christian Studies; Pontifical Institute of Mediaeval Studies","funders":"Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Buckling; Mathematical optimization; Regular polygon; Boundary (topology); Mathematics; Stability (learning theory); Set (abstract data type); Critical load; Boundary value problem; Optimization problem; Engineering design process; Structural engineering; Computer science; Engineering; Geometry; Mathematical analysis; Mechanical engineering","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":[0.001688475,0.001609843,0.001979957,0.001376348,0.0005055202,0.001199224,0.0009247296,0.001836702,0.00400901],"category_scores_gemma":[0.00530813,0.0009511858,0.0008128828,0.001554598,0.001516339,0.001598803,0.001728949,0.0009120269,0.0003463218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008114382,"about_ca_system_score_gemma":0.0005258755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002445582,"about_ca_topic_score_gemma":0.001527425,"domain_scores_codex":[0.9993474,0.0003061358,0.00002394011,0.00008409154,0.0001825087,0.00005596428],"domain_scores_gemma":[0.9983352,0.001324792,0.0001333819,0.00005796812,0.0001135079,0.0000350978],"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":[0.00001806325,0.000009908488,0.00005045497,0.0000578377,0.00001625667,0.00002508671,0.00001479549,0.984518,0.0004668868,0.008479316,0.0002888911,0.006054576],"study_design_scores_gemma":[0.000004449491,0.00002008526,0.00008735854,0.00001412536,0.000009313472,0.000008581725,0.000008877068,0.9831518,0.000219758,0.016027,0.0004410918,0.000007561856],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03859443,0.002368134,0.9298741,0.0007644045,0.0001612244,0.00007956137,0.0001670678,0.0001078201,0.02788331],"genre_scores_gemma":[0.8634615,0.005621746,0.1047496,0.0004820582,0.0004508897,0.0003466758,0.0003104161,0.0003376853,0.0242395],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00400901,"threshold_uncertainty_score":0.01341146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05933943060274317,"score_gpt":0.3382383270295422,"score_spread":0.278898896426799,"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."}}