{"id":"W2113481973","doi":"10.48550/arxiv.1212.2494","title":"Learning Generative Models of Similarity Matrices","year":2012,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Spectral clustering; Cluster analysis; Inference; Similarity (geometry); Pattern recognition (psychology); Mathematics; Data point; Artificial intelligence; Generative model; Computer science; Eigenvalues and eigenvectors; Algorithm; Generative grammar","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":[0.004568037,0.001075348,0.001681946,0.003046666,0.001218789,0.002921892,0.004805438,0.002596398,0.003735509],"category_scores_gemma":[0.02128483,0.001608645,0.002461168,0.002603201,0.002902023,0.004995317,0.003828488,0.003813392,0.001470123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001907689,"about_ca_system_score_gemma":0.0009992283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004586702,"about_ca_topic_score_gemma":0.006934184,"domain_scores_codex":[0.9963117,0.001402694,0.0001481438,0.001097825,0.0007862483,0.000253394],"domain_scores_gemma":[0.9891455,0.006927615,0.0008871214,0.001901771,0.0008216794,0.0003163303],"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":[0.00008901489,0.0001168418,0.004364021,0.0001407205,0.0001819996,0.0002344472,0.0007080259,0.4725347,0.002948093,0.4399843,0.003031046,0.07566686],"study_design_scores_gemma":[0.000006593779,0.00001188747,0.0002539831,0.0000122515,0.00001081587,0.00007612173,0.00002252299,0.8544856,0.0003813291,0.1440936,0.000628163,0.00001708368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006304961,0.0001035253,0.9925749,0.0001472543,0.00001388421,0.00002468895,0.00008089038,0.0001904142,0.0005594268],"genre_scores_gemma":[0.4915701,0.0006671245,0.4981569,0.0005526883,0.0002220847,0.0004898063,0.001443931,0.0003741851,0.006523222],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004805438,"threshold_uncertainty_score":0.02415842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08650278462184266,"score_gpt":0.1872110112214916,"score_spread":0.1007082265996489,"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."}}