{"id":"W2762764878","doi":"","title":"A posteriori finite element bounds with adaptive mesh refinement, application to outputs of the three dimensional convection-diffusion equation","year":2001,"lang":"en","type":"dissertation","venue":"TSpace (University of Toronto)","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"University of Toronto","keywords":"Finite element method; A priori and a posteriori; Adaptive mesh refinement; Convection–diffusion equation; Diffusion; Applied mathematics; Convection; Mathematics; Computer science; Mathematical optimization; Mechanics; Mathematical analysis; Computational science; Physics; Engineering; Structural engineering; Thermodynamics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003387479,0.001099637,0.001607983,0.0009037197,0.0009475473,0.001561309,0.001774681,0.002813124,0.002999625],"category_scores_gemma":[0.02212468,0.001070784,0.0008939609,0.0007461275,0.001864194,0.001172686,0.002487251,0.003074019,0.0006922959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009609784,"about_ca_system_score_gemma":0.00186605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0144564,"about_ca_topic_score_gemma":0.01069313,"domain_scores_codex":[0.9991857,0.000312419,0.00006464875,0.0001069902,0.0002731073,0.00005701141],"domain_scores_gemma":[0.9833953,0.01331363,0.0005462434,0.0006191998,0.001876785,0.0002488622],"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":[0.000343801,0.0001460529,0.00119494,0.0002372411,0.00005376327,0.0001034949,0.0003391191,0.8938326,0.01272166,0.01267776,0.001328864,0.07702076],"study_design_scores_gemma":[0.000005281831,0.00000619536,0.00004647473,0.000005243587,0.000001695674,0.000003987829,0.000004978202,0.9980791,0.0009689228,0.0007238187,0.0001508311,0.000003607286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01513781,0.0001176791,0.9832894,0.0001095626,0.00004091601,0.00002563889,0.00004067992,0.000484368,0.0007539496],"genre_scores_gemma":[0.3731767,0.0003033398,0.6207078,0.0001283851,0.00006134692,0.0002616831,0.0003364231,0.0008553142,0.00416892],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.0144564,"threshold_uncertainty_score":0.02874452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02166826041839947,"score_gpt":0.2298487908280769,"score_spread":0.2081805304096774,"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."}}