{"id":"W4291701058","doi":"10.1109/isncc55209.2022.9851764","title":"Transfer Learning for Behavioral Biometrics-based Continuous User Authentication","year":2022,"lang":"en","type":"article","venue":"2022 International Symposium on Networks, Computers and Communications (ISNCC)","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Public Health; Western University","funders":"","keywords":"Biometrics; Computer science; Authentication (law); Human–computer interaction; Transfer of learning; Computer security; Artificial intelligence","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":[0.0007118668,0.0002133315,0.0002349937,0.0004410862,0.001106845,0.0004565765,0.002761315,0.00006479432,0.00004012155],"category_scores_gemma":[0.00001592754,0.000241379,0.0001705413,0.0007931505,0.0001246558,0.0003055882,0.0007261548,0.0004213408,0.000007372513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001934002,"about_ca_system_score_gemma":0.00005744837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006462833,"about_ca_topic_score_gemma":0.00001066238,"domain_scores_codex":[0.9977878,0.0003753583,0.000517714,0.0005195928,0.0005163621,0.0002831234],"domain_scores_gemma":[0.9977347,0.0005913819,0.0001804212,0.001143437,0.0002312597,0.0001187564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002095143,0.003966498,0.00513633,0.00004502484,0.0004170188,0.000007250305,0.01587613,0.08736225,0.001205197,0.8056977,0.01059141,0.06948572],"study_design_scores_gemma":[0.0007947945,0.0002970537,0.0003977545,0.00001766938,0.0000219196,0.00001062634,0.0002084047,0.8296961,0.0000250201,0.0002096178,0.1680885,0.0002325577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03423879,0.0004765615,0.933408,0.02741386,0.00262086,0.001061007,0.0000592172,0.0003839589,0.0003377371],"genre_scores_gemma":[0.9926511,0.0001176956,0.004386314,0.001148255,0.00009072501,0.0004459499,0.0004617842,0.00002788547,0.0006703022],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9584123,"threshold_uncertainty_score":0.984315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02374180494258631,"score_gpt":0.2760372778010173,"score_spread":0.252295472858431,"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."}}