{"id":"W2026947217","doi":"10.1016/j.jcp.2009.03.022","title":"Verified predictions of shape sensitivities in wall-bounded turbulent flows by an adaptive finite-element method","year":2009,"lang":"en","type":"article","venue":"Journal of Computational Physics","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Sensitivity (control systems); Turbulence; Estimator; Finite element method; Convergence (economics); Grid; Bounded function; Flow (mathematics); Boundary (topology); Applied mathematics; Mathematics; Adaptive mesh refinement; Mathematical optimization; Computer science; Algorithm; Mathematical analysis; Geometry; Mechanics; Physics","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":[0.0009685903,0.000536131,0.0004344455,0.0004034877,0.0004012932,0.0006653678,0.0008504454,0.001107531,0.001084197],"category_scores_gemma":[0.004687903,0.0003768997,0.0004621692,0.0001761758,0.00086612,0.000602886,0.0008094153,0.0008183693,0.0001938598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004000638,"about_ca_system_score_gemma":0.0008028231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003057173,"about_ca_topic_score_gemma":0.001428155,"domain_scores_codex":[0.9996461,0.0001159699,0.00002025333,0.0000529371,0.0001360992,0.00002865601],"domain_scores_gemma":[0.9981627,0.0009912362,0.0001238427,0.0002044564,0.0004580397,0.00005976095],"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":[0.00005115507,0.00003302514,0.000632147,0.00002098281,0.000009253525,0.00004612515,0.00003317382,0.981092,0.007661502,0.004110176,0.0001181573,0.006192385],"study_design_scores_gemma":[0.000001806592,0.000003633216,0.00005023844,0.000001028567,7.094627e-7,0.000002169498,0.000001227814,0.9989432,0.0007586961,0.0002156162,0.00002012421,0.000001733385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2177877,0.00007033703,0.7754598,0.000187964,0.0000870672,0.00007597316,0.0000614173,0.0005824825,0.005687342],"genre_scores_gemma":[0.9502281,0.00002263797,0.04868681,0.00003559642,0.000009341173,0.00003808584,0.00003093382,0.00006280102,0.0008856583],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003057173,"threshold_uncertainty_score":0.00607878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06811778838996906,"score_gpt":0.3411245627884534,"score_spread":0.2730067743984844,"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."}}