{"id":"W4412049267","doi":"10.1016/j.eswa.2025.128920","title":"A comprehensive review on data-level methods for imbalanced data classification","year":2025,"lang":"en","type":"review","venue":"Expert Systems with Applications","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Artificial intelligence; Data classification; Data mining; Pattern recognition (psychology); 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":[0.004910303,0.001674041,0.003208997,0.006237285,0.0005389506,0.002453774,0.002624422,0.001435637,0.003762131],"category_scores_gemma":[0.0116399,0.000667889,0.001971331,0.00881183,0.0007624559,0.003359501,0.001371391,0.00238491,0.002566781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001078533,"about_ca_system_score_gemma":0.003474131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002569435,"about_ca_topic_score_gemma":0.003489877,"domain_scores_codex":[0.9977726,0.0004091581,0.0003431016,0.0004692197,0.0009195734,0.00008630522],"domain_scores_gemma":[0.9939599,0.003833994,0.0004137677,0.000235021,0.001443011,0.0001143362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005789732,0.00006524984,0.0004405896,0.01443928,0.0002099206,0.00003308177,0.00004084146,0.0007204143,0.0006190509,0.002793123,0.02342973,0.9571509],"study_design_scores_gemma":[0.00007694349,0.00032926,0.005230389,0.0238612,0.001785091,0.001047258,0.000191383,0.007521174,0.003574958,0.02438608,0.9318098,0.0001865396],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003001308,0.9824721,0.0144579,0.000683243,0.0005353109,0.00005717001,0.0002541312,0.000136466,0.001103547],"genre_scores_gemma":[0.002660471,0.9743241,0.01964784,0.000721676,0.0009907188,0.0001003609,0.0007669441,0.00005176668,0.0007361067],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006237285,"threshold_uncertainty_score":0.02596849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3769644452128858,"score_gpt":0.5124121553384758,"score_spread":0.13544771012559,"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."}}