{"id":"W4318977951","doi":"10.1007/978-3-031-10602-6_16","title":"Stochastic Neighbour Embedding","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Nonlinear dimensionality reduction; Embedding; Dimensionality reduction; Probabilistic logic; Manifold (fluid mechanics); Visualization; Computer science; Curse of dimensionality; Artificial intelligence; Space (punctuation); Mathematics; Pattern recognition (psychology); Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001524554,0.0003071593,0.0003212009,0.0001579324,0.0001296452,0.0002310505,0.0007932446,0.000185062,0.000492995],"category_scores_gemma":[0.00003270904,0.0002691189,0.0001825767,0.00005881451,0.00003785086,0.0002189465,0.0004841382,0.0002422166,0.0024976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003970103,"about_ca_system_score_gemma":0.00006852842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000101705,"about_ca_topic_score_gemma":0.00001152775,"domain_scores_codex":[0.9985741,0.00001308414,0.0002459349,0.0005707938,0.0003026717,0.0002934603],"domain_scores_gemma":[0.9988771,0.0001819911,0.0001209908,0.0006223862,0.00008739716,0.0001101326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001106404,0.000003107921,6.530248e-8,0.000006274314,0.00006785512,0.00003443024,0.00004578063,0.01155455,0.00001628507,0.9362912,0.02202624,0.02995313],"study_design_scores_gemma":[0.000179266,0.00007191938,0.000005527401,0.0001870501,0.00004464649,0.00001265367,0.000006693322,0.740575,0.00004751594,0.1867933,0.07116314,0.0009133029],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[4.508253e-8,0.00004578653,0.5761808,0.0002437616,0.0007731387,0.00008290184,0.000002972062,0.0002501322,0.4224205],"genre_scores_gemma":[0.001682351,0.00003092805,0.02221991,0.000289701,0.0006456632,0.000005953174,0.000006032487,0.00005541281,0.975064],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7494979,"threshold_uncertainty_score":0.9999761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02807336563847948,"score_gpt":0.2429042762714596,"score_spread":0.2148309106329802,"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."}}