{"id":"W4411565097","doi":"10.1007/978-981-96-6579-2_24","title":"Data Augmentation with Variational Autoencoder for Imbalanced Dataset","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Autoencoder; Computer science; Artificial intelligence; Machine learning; Pattern recognition (psychology); Data mining; Artificial neural network","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":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0009704062,0.0004175886,0.0003923249,0.0006485773,0.0002633437,0.0006012685,0.006828213,0.0002135905,0.00001384208],"category_scores_gemma":[0.0001534528,0.00037032,0.00003508465,0.0005660186,0.0003732283,0.001697524,0.001945603,0.0003954426,0.00001087119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003172884,"about_ca_system_score_gemma":0.001356478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001507644,"about_ca_topic_score_gemma":0.00008900764,"domain_scores_codex":[0.996082,0.00002660103,0.0005097714,0.002072732,0.0008571144,0.0004517566],"domain_scores_gemma":[0.9947515,0.0006388219,0.0004059731,0.003782906,0.0003332084,0.00008757367],"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":[0.00004894632,0.00008688105,0.00005205731,0.0001585124,0.000055225,0.00001917275,0.0001752227,0.01392658,0.0001785287,0.2578194,0.01759583,0.7098836],"study_design_scores_gemma":[0.0004123696,0.0001065807,0.0001414456,0.0002334011,0.00001477637,0.00001539845,6.739677e-8,0.8883804,0.0004590865,0.08271229,0.02706813,0.0004560396],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[1.774583e-7,0.00005419102,0.9911843,0.001838213,0.0006381315,0.0009049909,0.00443676,0.0002571978,0.0006860625],"genre_scores_gemma":[0.000342526,0.0000219014,0.9883007,0.002029246,0.0001854635,0.0000667143,0.008695273,0.00002023876,0.0003379109],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8744538,"threshold_uncertainty_score":0.9998749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03483581431491785,"score_gpt":0.3048072481334428,"score_spread":0.269971433818525,"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."}}