{"id":"W4413944941","doi":"10.1016/j.neucom.2025.131441","title":"Anchor-aware representation learning for multi-view clustering","year":2025,"lang":"en","type":"article","venue":"Neurocomputing","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Key Laboratory of Synthetic and Natural Functional Molecular Chemistry; Sichuan Province Science and Technology Support Program; Ministry of Natural Resources","keywords":"Computer science; Cluster analysis; Artificial intelligence; Representation (politics); Feature learning; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000174242,0.000101084,0.0001259532,0.000112071,0.0003375466,0.0001766606,0.0003051725,0.00004340062,0.000001967139],"category_scores_gemma":[0.0001227634,0.0001041752,0.00006831656,0.0003260134,0.000008340153,0.0002731888,0.0002835235,0.0001521565,0.00001463641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001709878,"about_ca_system_score_gemma":0.00002293817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008102984,"about_ca_topic_score_gemma":0.00000235868,"domain_scores_codex":[0.9989741,0.00007770174,0.0002224802,0.0004034865,0.00009762938,0.0002246078],"domain_scores_gemma":[0.9993926,0.0001986764,0.00008997603,0.0001968302,0.00008716524,0.00003477236],"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":[0.000008850413,0.00004119037,0.002051154,0.0001774994,0.00001049193,0.00000556547,0.0004326719,0.02861128,0.007392634,0.0004431818,0.001337214,0.9594883],"study_design_scores_gemma":[0.0004522876,0.00002521515,0.001893401,0.0001959264,0.00000406883,0.000003278298,0.00004612563,0.9861792,0.004554032,0.0001623561,0.006384537,0.00009959705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01590187,0.00005731474,0.9819533,0.0004351588,0.0005671114,0.0003017806,2.591194e-7,0.0003098991,0.0004733489],"genre_scores_gemma":[0.8404465,0.00002141265,0.1574426,0.001203716,0.0001262402,0.00005775173,0.000009156052,0.00001440118,0.0006782372],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9593887,"threshold_uncertainty_score":0.4248143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05526431671058828,"score_gpt":0.342538638952467,"score_spread":0.2872743222418787,"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."}}