{"id":"W1591713534","doi":"10.1007/978-3-540-76414-4_22","title":"Cumulative Global Distance for Dimension Reduction in Handwritten Digits Database","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Mahalanobis distance; Bhattacharyya distance; Principal component analysis; Computer science; Pattern recognition (psychology); Dimension (graph theory); Eigenvalues and eigenvectors; Dimensionality reduction; Mathematics; Statistics; Artificial intelligence; Combinatorics","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":[0.0005505573,0.000643432,0.001134808,0.001642743,0.0004655074,0.000871967,0.0009791184,0.000441802,0.002794076],"category_scores_gemma":[0.001615167,0.0001994612,0.0007014013,0.001740761,0.0002794842,0.0008608449,0.0008364684,0.0006531668,0.0009771367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004769335,"about_ca_system_score_gemma":0.001023987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00477718,"about_ca_topic_score_gemma":0.005663444,"domain_scores_codex":[0.9992166,0.0001160518,0.00006960516,0.0001706548,0.0003399129,0.00008715369],"domain_scores_gemma":[0.9993275,0.0001587034,0.00003369635,0.000179039,0.0002672908,0.00003371882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005634344,0.0001152735,0.001606415,0.0001608427,0.00007066502,0.00006601684,0.00005196984,0.02171368,0.01799826,0.003460616,0.01725248,0.9369403],"study_design_scores_gemma":[0.00007490194,0.0004527369,0.01137618,0.00004787255,0.0001337807,0.000433805,0.0001951547,0.8951297,0.06088487,0.01251546,0.01867678,0.00007882588],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1694044,0.006672366,0.8121071,0.0004425992,0.000436379,0.0001378357,0.002683361,0.004027493,0.004088452],"genre_scores_gemma":[0.4814782,0.002387588,0.493216,0.0001238085,0.0002296183,0.0002053639,0.01063154,0.0003350315,0.01139288],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00477718,"threshold_uncertainty_score":0.009498775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03319452533194676,"score_gpt":0.2963947199267133,"score_spread":0.2632001945947666,"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."}}