{"id":"W4416677236","doi":"10.1109/dsaa65442.2025.11247986","title":"Scalable Deep Subspace Clustering Network","year":2025,"lang":"","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Cluster analysis; Pattern recognition (psychology); Subspace topology; Spectral clustering; Pairwise comparison; Computational complexity theory; Correlation clustering; Feature (linguistics); Bottleneck","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":[0.0007165236,0.001270224,0.00164675,0.001003594,0.0009372664,0.001191077,0.002598047,0.001538546,0.007375636],"category_scores_gemma":[0.002375799,0.00055948,0.0010689,0.001859465,0.0009040172,0.002495587,0.002503455,0.001672419,0.002503342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002064418,"about_ca_system_score_gemma":0.002393011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01464155,"about_ca_topic_score_gemma":0.02626553,"domain_scores_codex":[0.9990574,0.0001810809,0.00003340619,0.0003263845,0.0002465344,0.0001552801],"domain_scores_gemma":[0.9991879,0.0001911716,0.00005908879,0.0001899385,0.0002918483,0.00008013171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002207514,0.0001205614,0.001019296,0.0001111752,0.0001126927,0.0001346919,0.00008519651,0.6903237,0.005067911,0.03617308,0.02966774,0.2369632],"study_design_scores_gemma":[0.000004938403,0.000009622919,0.00006779237,0.000002829163,0.000004101876,0.00001308571,0.000009753068,0.9889419,0.000746733,0.008991425,0.001201673,0.000006008079],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02033251,0.0004961923,0.9677114,0.000615565,0.0000983227,0.00008554547,0.001075941,0.00376251,0.005821992],"genre_scores_gemma":[0.5088149,0.0007361838,0.4541951,0.0007592102,0.0001801709,0.0004782926,0.008103546,0.0006197297,0.02611293],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01464155,"threshold_uncertainty_score":0.02911264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01253013401121324,"score_gpt":0.2461978347078214,"score_spread":0.2336677006966082,"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."}}