{"id":"W7127269602","doi":"10.1109/ism66958.2025.00048","title":"An Efficient Optimization Criterion for Multi-View Feature Representation Learning","year":2025,"lang":"","type":"article","venue":"","topic":"Face recognition and analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Wilfrid Laurier University","funders":"","keywords":"Generalizability theory; Bottleneck; Representation (politics); Feature learning; Deep learning; Artificial neural network; Feature (linguistics); External Data Representation; Face (sociological concept)","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":[0.00226733,0.001470401,0.001562118,0.000813465,0.000430919,0.001019902,0.001384864,0.001643777,0.002277774],"category_scores_gemma":[0.005338281,0.0006312245,0.0009072237,0.0009611506,0.0008014972,0.001667124,0.001704395,0.001817639,0.0009596568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007325631,"about_ca_system_score_gemma":0.001127184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001422467,"about_ca_topic_score_gemma":0.001103806,"domain_scores_codex":[0.9987923,0.0004468994,0.0000887311,0.0002475287,0.0003405364,0.00008403841],"domain_scores_gemma":[0.9986948,0.0006696746,0.0001031142,0.0001213318,0.0003546195,0.00005642226],"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":[0.0001402972,0.0001234403,0.000615348,0.0003020406,0.00008963244,0.0001472401,0.00008721335,0.6776804,0.01723703,0.03207582,0.006876508,0.2646251],"study_design_scores_gemma":[0.000005842103,0.0000483626,0.00007412485,0.000007914548,0.00000534421,0.0000352375,0.000006376924,0.9922929,0.001498197,0.005450939,0.0005656233,0.0000091554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001849098,0.0001259065,0.9974493,0.00006711402,0.0000121927,0.00002321822,0.00002185983,0.0001024886,0.000348721],"genre_scores_gemma":[0.2581123,0.000426219,0.7375015,0.0002286518,0.0001225057,0.0004278517,0.0005007472,0.0002644718,0.002415731],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002277774,"threshold_uncertainty_score":0.01199096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03623561550136797,"score_gpt":0.3547986217941241,"score_spread":0.3185630062927561,"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."}}