{"id":"W2625688128","doi":"","title":"The Privacy/Security Tradeoff for Multiple Secure Sketch Biometric Authentication Systems","year":2015,"lang":"en","type":"dissertation","venue":"TSpace","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biometrics; Computer security; Sketch; Computer science; Authentication (law); Internet privacy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00150266,0.0004097453,0.0004637789,0.0004643908,0.0005237756,0.001080896,0.00239701,0.0004276829,0.000003526919],"category_scores_gemma":[0.0007986417,0.0003198043,0.0002337241,0.001458989,0.00004397218,0.0002817641,0.00009280987,0.0003347032,0.000131875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002109951,"about_ca_system_score_gemma":0.0003963271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001771335,"about_ca_topic_score_gemma":0.0002826909,"domain_scores_codex":[0.9968057,0.0002502421,0.0006775361,0.0007797484,0.000942797,0.000544007],"domain_scores_gemma":[0.9959067,0.0006325798,0.0007263281,0.001638215,0.0008469295,0.0002492728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001349802,0.0005114468,0.0001759424,0.002053022,0.0004087465,0.000003959776,0.7682167,0.000005327645,0.0009867811,0.1056713,0.1115208,0.0103111],"study_design_scores_gemma":[0.001344751,0.0001782167,0.001260245,0.0002536115,0.000136562,0.00001609905,0.01441234,0.3712586,0.0006976106,0.009990425,0.5994744,0.000977208],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6825808,0.0566133,0.138542,0.01635274,0.06149502,0.02786139,0.0003613512,0.004119242,0.0120742],"genre_scores_gemma":[0.975473,0.00009952286,0.0003840353,0.00002592309,0.0003302622,0.0006738253,0.0005888208,0.00005760725,0.022367],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7538043,"threshold_uncertainty_score":0.9999561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03819500174289071,"score_gpt":0.3479060020362641,"score_spread":0.3097110002933734,"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."}}