{"id":"W2162049453","doi":"10.1109/ccst.2000.891166","title":"Securing information and operations in a smart card through biometrics","year":2002,"lang":"en","type":"article","venue":"","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute of Steel Construction","keywords":"Biometrics; Smart card; Computer science; MULTOS; Iris recognition; Hand geometry; Authentication (law); OpenPGP card; Identification (biology); Smart card application protocol data unit; Computer security; Task (project management); Biometric data; Card reader; Terminal (telecommunication); Human–computer interaction; Embedded system; Credit card; World Wide Web; Engineering; Computer network","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006014795,0.0003412851,0.0005214441,0.000636254,0.000435928,0.001434029,0.0006556526,0.0008250653,0.004514089],"category_scores_gemma":[0.00144711,0.0002152103,0.0002394109,0.0006587388,0.0008269677,0.002599998,0.0006396028,0.0004144052,0.00325564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002325185,"about_ca_system_score_gemma":0.000295868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004784616,"about_ca_topic_score_gemma":0.0003353781,"domain_scores_codex":[0.9991869,0.0001276911,0.00006827756,0.0001359533,0.0004181714,0.00006295478],"domain_scores_gemma":[0.9991236,0.0001478359,0.00008606782,0.0003568961,0.0002469616,0.00003862495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001047593,0.0002264956,0.003781147,0.0003859209,0.00004659689,0.0006869989,0.000577421,0.003823334,0.4105008,0.0503221,0.0049782,0.5236233],"study_design_scores_gemma":[0.000176557,0.001861516,0.007430634,0.0001803383,0.0001394179,0.005363943,0.0002860004,0.07146594,0.7313226,0.0143244,0.1672695,0.0001790795],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1272135,0.001327507,0.8429845,0.000443248,0.0003806184,0.0003297538,0.0001896614,0.00570203,0.02142919],"genre_scores_gemma":[0.5628994,0.00122601,0.4090708,0.0002536705,0.00008716241,0.0001082351,0.000258843,0.000140681,0.02595514],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004514089,"threshold_uncertainty_score":0.01510113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0295876029319655,"score_gpt":0.234115885196338,"score_spread":0.2045282822643725,"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."}}