{"id":"W4405865884","doi":"10.1016/j.neunet.2024.107099","title":"Simplified PCNet with robustness","year":2024,"lang":"en","type":"article","venue":"Neural Networks","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"National Natural Science Foundation of China","keywords":"Robustness (evolution); Computer science; Artificial intelligence; Machine learning","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":[0.0008146344,0.001420757,0.0009820884,0.0009718626,0.0006676918,0.001601662,0.002310328,0.001562322,0.01671124],"category_scores_gemma":[0.005171427,0.0006691244,0.0007799615,0.0007403797,0.0006930042,0.002514698,0.002083814,0.001838871,0.006941718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006986118,"about_ca_system_score_gemma":0.001659833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01150575,"about_ca_topic_score_gemma":0.01057996,"domain_scores_codex":[0.9992723,0.00009012084,0.00004425625,0.00023829,0.0002576937,0.00009734104],"domain_scores_gemma":[0.9985812,0.0002018894,0.00004396634,0.0006749916,0.0004437363,0.00005420644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006538199,0.0001551519,0.0009548029,0.0001990134,0.0001658948,0.0003138636,0.0000369952,0.4559887,0.01806201,0.04027919,0.02637063,0.4568199],"study_design_scores_gemma":[0.00002007966,0.00003689335,0.0002282584,0.00001093561,0.00002527297,0.00008926605,0.000006142421,0.9698901,0.008836568,0.01558204,0.005260126,0.00001431112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01851059,0.0004849973,0.9468484,0.0006454614,0.0006015053,0.0001378672,0.001052948,0.01416497,0.01755326],"genre_scores_gemma":[0.4921812,0.0004230263,0.4694468,0.0005748534,0.0003855554,0.0002985784,0.003246497,0.002027997,0.03141548],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01671124,"threshold_uncertainty_score":0.05590463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01053770745339577,"score_gpt":0.2334969131562819,"score_spread":0.2229592057028862,"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."}}