{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001181144,0.00004543119,0.00005957948,0.000254505,0.00005534654,0.0002658175,0.0001592779,0.00002743598,0.00001661285],"category_scores_gemma":[0.00003275821,0.00004136163,0.00001131677,0.0008872368,0.00001005844,0.00170312,0.00006561948,0.00004102154,0.0001080414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001858005,"about_ca_system_score_gemma":0.00000607766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002243977,"about_ca_topic_score_gemma":0.0001110869,"domain_scores_codex":[0.9994941,0.00002110388,0.0001851084,0.00008805095,0.0001197271,0.00009193357],"domain_scores_gemma":[0.9997214,0.00002032012,0.00001698994,0.0001743684,0.00003684626,0.00003004716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[7.524528e-7,0.0001379218,0.01258139,0.00007256163,0.0000158293,0.000002937994,0.4870616,0.00005505294,0.0001153988,0.4646094,0.002166976,0.03318015],"study_design_scores_gemma":[0.0002714496,0.00001629881,0.00370395,0.00000840239,0.000001013331,0.00001019552,0.0002874269,0.96553,0.0001520281,0.0004703859,0.02944619,0.0001026068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3499047,0.0003846854,0.6195402,0.004547663,0.0004003378,0.0004164687,0.000002932891,0.0002505667,0.02455248],"genre_scores_gemma":[0.9947134,0.00005189005,0.004683195,0.0003843163,0.00000656123,0.000008868611,0.000001492302,0.000001182873,0.0001491505],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.965475,"threshold_uncertainty_score":0.2563285,"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."}}