{"id":"W4413371190","doi":"10.1109/tfuzz.2025.3596066","title":"CS3W-GBG: A Cost-Sensitive Three-Way Granular-Ball Generation Method","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Fuzzy Systems","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Ball (mathematics); Artificial intelligence; Mathematics; Geometry","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":[],"consensus_categories":[],"category_scores_codex":[0.0004704108,0.0002495764,0.0003179472,0.0003837243,0.000458477,0.0002939012,0.0004148912,0.0001052608,0.000005385866],"category_scores_gemma":[0.000009450169,0.0002354804,0.0001602233,0.0008134714,0.00003905429,0.0006062802,0.000004876247,0.0003114212,0.0001196561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001707977,"about_ca_system_score_gemma":0.00009396222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001679941,"about_ca_topic_score_gemma":0.000108495,"domain_scores_codex":[0.9979597,0.0002838022,0.000418012,0.0006374403,0.0003565719,0.0003444253],"domain_scores_gemma":[0.9986361,0.0001960283,0.0001041046,0.0007174697,0.0002275665,0.0001187156],"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":[0.0000486912,0.0003133666,0.00001631929,0.00009091854,0.0001465991,0.00004571957,0.0008329965,0.1235552,0.05001026,0.02245888,0.002042419,0.8004386],"study_design_scores_gemma":[0.0006975374,0.00007007115,0.0000696918,0.0001489275,0.0000304975,0.00003863364,0.0001070792,0.9528911,0.03864573,0.000596926,0.00641157,0.0002923027],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000194843,0.0001628254,0.989759,0.0008059436,0.004211523,0.0007150827,0.00001683616,0.0003586695,0.003775265],"genre_scores_gemma":[0.8919365,0.00003605103,0.1041455,0.0009073545,0.0001303817,0.0002017324,0.000004266819,0.00002397678,0.002614217],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8917416,"threshold_uncertainty_score":0.9602613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03019031990350301,"score_gpt":0.309873240771242,"score_spread":0.279682920867739,"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."}}