{"id":"W2049505818","doi":"10.1109/bcc.2007.4430530","title":"Face Based Biometric Authentication with Changeable and Privacy Preservable Templates","year":2007,"lang":"en","type":"article","venue":"","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Biometrics; Computer science; Authentication (law); Face (sociological concept); Key (lock); Orthonormal basis; Information privacy; Transformation (genetics); Invertible matrix; Data mining; Theoretical computer science; Artificial intelligence; Computer security; 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":[0.0007141422,0.00008591837,0.0000860298,0.001038364,0.0001265463,0.0002570412,0.0004411278,0.00004979068,0.00004544549],"category_scores_gemma":[0.0000701313,0.00006552509,0.00001440217,0.004820434,0.00004103289,0.0004800263,0.0001037971,0.00005223265,0.00004123956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002595067,"about_ca_system_score_gemma":0.00003198938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001226132,"about_ca_topic_score_gemma":0.00001541409,"domain_scores_codex":[0.9990075,0.00001938687,0.0001507721,0.0003158082,0.0002769534,0.0002296101],"domain_scores_gemma":[0.9991072,0.0001321562,0.00006907558,0.0004633667,0.0001149838,0.0001131485],"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":[0.0001515822,0.002595735,0.1282073,0.0006275215,0.0002009605,0.00004553849,0.008559948,0.00004976074,0.0242127,0.2758504,0.01963717,0.5398613],"study_design_scores_gemma":[0.001775749,0.0003361474,0.3587218,0.00003061762,0.00002341988,0.00002964531,0.0001734023,0.4053251,0.09355703,0.001653829,0.13766,0.0007133126],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06714163,0.0001842518,0.9293804,0.001319287,0.00006494798,0.0002068606,0.000001243673,0.0001655374,0.001535878],"genre_scores_gemma":[0.9103256,0.000008407121,0.08723009,0.0001734808,0.00001060418,0.000006744344,0.000006075215,0.000004581145,0.002234391],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.843184,"threshold_uncertainty_score":0.2672036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02740355720544886,"score_gpt":0.2545595567448627,"score_spread":0.2271559995394139,"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."}}