{"id":"W2795588493","doi":"10.1007/978-3-319-89656-4_19","title":"Dimensionality Reduction and Visualization by Doubly Kernelized Unit Ball Embedding","year":2018,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Cluster analysis; Dimensionality reduction; Computer science; Embedding; Visualization; Graph embedding; Kernel (algebra); Pattern recognition (psychology); Gaussian function; Algorithm; Gaussian; Artificial intelligence; Data mining; Mathematics; Discrete mathematics","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":[0.0003643998,0.0007895416,0.0009283074,0.0009618578,0.0003270666,0.001586775,0.0008768322,0.0005313379,0.006105219],"category_scores_gemma":[0.001900609,0.0003623784,0.0007493061,0.001043061,0.0004500654,0.001551419,0.001961936,0.001356057,0.002774291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002943414,"about_ca_system_score_gemma":0.0006506159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001938263,"about_ca_topic_score_gemma":0.001667096,"domain_scores_codex":[0.9995655,0.0001066076,0.00002685339,0.000085632,0.0001625605,0.00005281207],"domain_scores_gemma":[0.999453,0.0001107919,0.00004037122,0.0001769005,0.0001747312,0.00004418033],"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":[0.0003416871,0.0001239856,0.0006056149,0.0002466619,0.00007208935,0.00009650578,0.0002685181,0.04031428,0.05426578,0.03991538,0.03640172,0.8273478],"study_design_scores_gemma":[0.00001851591,0.00006048584,0.0006134105,0.00002396882,0.0000153715,0.0001504494,0.00008897602,0.9355072,0.02320253,0.02707711,0.01320579,0.00003620037],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01027692,0.0002861956,0.9851009,0.0002326949,0.00009327511,0.00003842362,0.0002944563,0.002301926,0.001375267],"genre_scores_gemma":[0.2060681,0.0008146744,0.7812262,0.0001441971,0.0001050621,0.0002048586,0.001761814,0.001176686,0.008498248],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006105219,"threshold_uncertainty_score":0.02042395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02188198916773889,"score_gpt":0.2866329445835294,"score_spread":0.2647509554157905,"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."}}