{"id":"W2987569708","doi":"10.1016/j.apm.2019.10.035","title":"Techniques for approximating a spatially varying Euler-Bernoulli model with a constant coefficient model","year":2019,"lang":"en","type":"article","venue":"Applied Mathematical Modelling","topic":"Vibration and Dynamic Analysis","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Air Force Office of Scientific Research; Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Constant coefficients; Mathematical analysis; Inverse problem; Constant (computer programming); Boundary value problem; Finite element method; Bernoulli's principle; Applied mathematics; Physics; Computer 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002818902,0.0003022111,0.0004983217,0.000116509,0.0001006987,0.00008286256,0.0001757192,0.0001280912,0.0000241885],"category_scores_gemma":[0.000008628996,0.0002548166,0.0001080112,0.0001684598,0.00004202199,0.0001030147,0.00003619548,0.0001883166,0.00003077008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007481466,"about_ca_system_score_gemma":0.0000454031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.065189e-7,"about_ca_topic_score_gemma":6.233077e-7,"domain_scores_codex":[0.9983608,0.000005193287,0.0005562675,0.0003503911,0.0003177535,0.0004095639],"domain_scores_gemma":[0.9992175,0.0001613447,0.00009331755,0.0003483795,0.00006967122,0.0001097551],"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":[0.0000213341,0.00004364541,3.641618e-7,0.0003980935,0.00004902521,2.823006e-7,0.000504758,0.807442,0.002191293,0.1888711,0.000006102127,0.0004720174],"study_design_scores_gemma":[0.0003524189,0.00002022489,2.873078e-9,0.0001305124,0.00007893122,0.000002500408,0.00007821789,0.9271487,0.002045651,0.06980585,0.000004155388,0.000332835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005212618,0.00001313914,0.9593881,0.00002544561,0.00001152394,0.001059077,0.0000135817,0.0006606776,0.03361585],"genre_scores_gemma":[0.5173416,0.000003909454,0.4822844,0.00003856938,0.00001119335,0.0001909807,0.0000124232,0.0000567183,0.00006026266],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5121289,"threshold_uncertainty_score":0.9999904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01606749946945382,"score_gpt":0.2151031333927784,"score_spread":0.1990356339233246,"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."}}