{"id":"W2108081861","doi":"10.2514/6.2007-1297","title":"Functional Outputs Error Based Mesh Adaptation","year":2007,"lang":"en","type":"article","venue":"45th AIAA Aerospace Sciences Meeting and Exhibit","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Adaptation (eye); Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0008661959,0.0001371789,0.0001255249,0.0000735045,0.0005777705,0.0001092577,0.00008420147,0.00003758227,0.0001883438],"category_scores_gemma":[0.00001345699,0.0001167553,0.00005926052,0.0003142538,0.0001992712,0.0001856749,0.00002759427,0.0001353054,0.00002276946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001210453,"about_ca_system_score_gemma":0.00006523766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000151191,"about_ca_topic_score_gemma":0.00002433281,"domain_scores_codex":[0.9987511,0.00003267872,0.0001832022,0.0003607807,0.0003123564,0.0003598666],"domain_scores_gemma":[0.9994937,0.00009503412,0.0001102125,0.00009329501,0.00005691593,0.0001508553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004472491,0.0005905743,0.3221036,0.00008685589,0.0001027779,0.00001001977,0.004341976,0.2278491,0.03362776,0.1481415,0.04090531,0.2217933],"study_design_scores_gemma":[0.004424359,0.0008382528,0.05584363,0.0005075625,0.0001338495,0.00001997787,0.02081066,0.8139712,0.0633145,0.005646979,0.03212959,0.002359416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8449658,0.0001476854,0.1177304,0.001715266,0.0008237003,0.0001586799,0.000004370764,0.0000930114,0.03436104],"genre_scores_gemma":[0.9946635,0.000002242138,0.003119261,0.0002147336,0.000444603,0.000005025825,0.000009444789,0.000007837155,0.001533361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5861222,"threshold_uncertainty_score":0.4761144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04097731743427872,"score_gpt":0.2736835362972424,"score_spread":0.2327062188629637,"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."}}