{"id":"W4410932871","doi":"10.1002/cjs.70013","title":"A deep support vector clustering algorithm for unsupervised and semi‐supervised learning","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Cluster analysis; Artificial intelligence; Computer science; Unsupervised learning; Pattern recognition (psychology); Semi-supervised learning; Machine learning; Algorithm","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002934798,0.001100775,0.001576155,0.002194671,0.0009951418,0.001306626,0.003298998,0.001995718,0.00319483],"category_scores_gemma":[0.006407664,0.0007913965,0.001437976,0.001924642,0.00123011,0.001828756,0.002326882,0.002947024,0.001638106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001524958,"about_ca_system_score_gemma":0.002039041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005017909,"about_ca_topic_score_gemma":0.004666398,"domain_scores_codex":[0.9979544,0.0005917452,0.0001503511,0.0005691323,0.0005672996,0.0001669742],"domain_scores_gemma":[0.996609,0.001204531,0.0003213085,0.0005426057,0.001154148,0.0001683148],"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":[0.0002312625,0.0001612131,0.001212504,0.0001079612,0.0001473495,0.00007104097,0.000158589,0.5068116,0.004029945,0.02540062,0.006651874,0.4550161],"study_design_scores_gemma":[0.000004359858,0.00001140417,0.00004340598,0.000003593906,0.000002087469,0.000009029203,0.000005879276,0.9954786,0.0005253555,0.003641414,0.0002706948,0.000004274536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005877203,0.0001027222,0.9926393,0.00009466537,0.00002418166,0.00005811316,0.00005322211,0.0007257099,0.0004248863],"genre_scores_gemma":[0.224132,0.0001234062,0.7707378,0.0001955909,0.00007699567,0.0003206588,0.0007947737,0.0003079336,0.003310878],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005017909,"threshold_uncertainty_score":0.01552087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01362715295564086,"score_gpt":0.231920992576553,"score_spread":0.2182938396209122,"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."}}