{"id":"W4400680796","doi":"10.1109/cefc61729.2024.10586063","title":"Mesh Error Estimation Using Graph Neural Networks","year":2024,"lang":"en","type":"article","venue":"","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Artificial neural network; Estimation; Graph; Theoretical computer science; Artificial intelligence; Algorithm; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006452159,0.0007778436,0.000621111,0.001571274,0.0002710507,0.0007261384,0.00117078,0.001253721,0.001429891],"category_scores_gemma":[0.004264068,0.000510372,0.0005369633,0.0008999282,0.0004820447,0.001066451,0.0007570079,0.000877052,0.0004906981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007616233,"about_ca_system_score_gemma":0.0004994222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01025313,"about_ca_topic_score_gemma":0.01243824,"domain_scores_codex":[0.9996153,0.00007810115,0.00001964455,0.0001196188,0.0001353177,0.00003192735],"domain_scores_gemma":[0.998735,0.0006197351,0.0001432932,0.0001510862,0.0003171334,0.00003362679],"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":[0.00006978171,0.00002254579,0.001428921,0.00003843845,0.00003475872,0.0000328366,0.00001747137,0.8995802,0.002748476,0.002273157,0.001012852,0.09274053],"study_design_scores_gemma":[0.000001271513,0.000003442818,0.0001254485,0.000002658342,0.00000165057,0.000004530166,0.000001781488,0.9981255,0.0004591786,0.001174985,0.00009750103,0.000002068215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02586007,0.0002270673,0.9714243,0.0001274153,0.00004544579,0.00002465245,0.0001097751,0.001202804,0.0009784503],"genre_scores_gemma":[0.7154393,0.0002659472,0.2799439,0.0001349987,0.0000482525,0.00007451226,0.0005336817,0.000266523,0.003292894],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01025313,"threshold_uncertainty_score":0.02038687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03162838175913973,"score_gpt":0.2689607012784612,"score_spread":0.2373323195193214,"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."}}