{"id":"W2099082374","doi":"10.1109/ccece.2003.1226343","title":"A modified PCA algorithm for face recognition","year":2004,"lang":"en","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Yale University; Minnesota Pollution Control Agency","keywords":"Principal component analysis; Eigenvalues and eigenvectors; Facial recognition system; Pattern recognition (psychology); Linear discriminant analysis; Face (sociological concept); Artificial intelligence; Computer science; Feature (linguistics); Computation; Feature extraction; Feature vector; Algorithm; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009244181,0.00007611062,0.00007329049,0.00005611287,0.0000932933,0.00008410078,0.0002094228,0.00005455172,0.00002032928],"category_scores_gemma":[0.00001482342,0.00006476433,0.00005458443,0.0001275565,0.000009804971,0.000456981,0.00004532732,0.00004412732,0.0002616879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002201566,"about_ca_system_score_gemma":0.00003155531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002636707,"about_ca_topic_score_gemma":0.000003674687,"domain_scores_codex":[0.9993526,0.000009893067,0.000115109,0.0002368212,0.0001131411,0.0001724149],"domain_scores_gemma":[0.9996278,0.0000316792,0.00003258016,0.0001687284,0.00007867733,0.00006054514],"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":[0.000002991408,0.00005695145,2.481795e-7,0.000004846255,0.0000046928,0.000001458962,0.0001701819,0.0001625265,0.001344683,0.002189378,0.001875625,0.9941864],"study_design_scores_gemma":[0.003959857,0.0003664648,0.00005819139,0.0001049491,0.00001250525,0.00003028937,0.0002084552,0.3756455,0.2439481,0.3670848,0.007984091,0.000596849],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003115543,0.00001323308,0.9907109,0.001192098,0.0002688557,0.0002488322,0.000009360779,0.0002329769,0.004208219],"genre_scores_gemma":[0.07209626,0.00001556362,0.9255352,0.001247368,0.0000736703,0.0001309583,0.00003776971,0.000007863119,0.0008553716],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9935896,"threshold_uncertainty_score":0.3363557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03997030804081896,"score_gpt":0.2626470876825613,"score_spread":0.2226767796417424,"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."}}