{"id":"W7164025617","doi":"10.1109/icdabi67967.2025.11547663","title":"Enhancing Manifold Convexity in Deep MRI Image Clustering Using Adversarial Learning","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Cluster analysis; Adversarial system; Pattern recognition (psychology); Image (mathematics); Deep learning; Manifold (fluid mechanics); Convexity; Nonlinear dimensionality reduction","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":[0.0008261336,0.0007958156,0.0007389477,0.0005070103,0.0003380039,0.0006496728,0.0009149937,0.0009794123,0.001075594],"category_scores_gemma":[0.002020039,0.0004420937,0.0008946656,0.0002862757,0.001137473,0.0008667599,0.001281418,0.001434817,0.0003056454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009557428,"about_ca_system_score_gemma":0.0006794284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006199973,"about_ca_topic_score_gemma":0.005770984,"domain_scores_codex":[0.9997525,0.00007646383,0.0000101547,0.00006399133,0.00005551653,0.00004140641],"domain_scores_gemma":[0.9993894,0.0003176967,0.00009120149,0.00006906912,0.00009015066,0.00004240131],"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":[0.00004676378,0.0000145865,0.0004587171,0.00002228108,0.00002017763,0.00004388746,0.00003271438,0.9771801,0.002341287,0.005038142,0.0005203948,0.01428107],"study_design_scores_gemma":[0.000001080666,0.000007772859,0.00005206086,0.000002378596,0.000001558728,0.000008589997,0.000002135075,0.9982974,0.0003780378,0.001141317,0.0001052783,0.000002412119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06758561,0.0004663351,0.9282416,0.0004605553,0.00005351937,0.0000344043,0.00008482645,0.000644712,0.0024284],"genre_scores_gemma":[0.8951389,0.0004526263,0.09815098,0.0003058093,0.00004984479,0.00006620133,0.0002595843,0.0001420872,0.005433992],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006199973,"threshold_uncertainty_score":0.01232779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0165785327877702,"score_gpt":0.2887027238916425,"score_spread":0.2721241911038723,"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."}}