{"id":"W1998448825","doi":"10.1145/2076732.2076756","title":"Dynamic sample size detection in continuous authentication using sequential sampling","year":2011,"lang":"en","type":"article","venue":"","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Authentication (law); Session (web analytics); Biometrics; Process (computing); Sampling (signal processing); Sample (material); Scheme (mathematics); Data mining; Real-time computing; Artificial intelligence; Computer security; Computer vision; Operating system; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004431911,0.0005556393,0.0007734026,0.001162204,0.0005405317,0.0008059054,0.001352962,0.0008846717,0.0009986564],"category_scores_gemma":[0.0191946,0.0005244101,0.0004003242,0.0008333276,0.001785332,0.001851463,0.001279918,0.000865268,0.0003202662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008646557,"about_ca_system_score_gemma":0.0007642774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002199277,"about_ca_topic_score_gemma":0.001736972,"domain_scores_codex":[0.9969112,0.001125705,0.0001099901,0.0005833007,0.001117295,0.0001524556],"domain_scores_gemma":[0.9845964,0.01125533,0.001139967,0.001603693,0.001108433,0.0002961767],"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":[0.002256003,0.0004413821,0.01725204,0.0003022126,0.0001349108,0.0006096746,0.0009118566,0.3648127,0.08973825,0.05869307,0.001561734,0.4632862],"study_design_scores_gemma":[0.00002644808,0.0002074937,0.001275014,0.00001024894,0.00001393567,0.000231004,0.00002712787,0.9820154,0.008425182,0.007242988,0.0004988359,0.00002637848],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03167464,0.0001147328,0.9673159,0.00006171238,0.00002446168,0.00004011912,0.00001235472,0.0002819629,0.0004741588],"genre_scores_gemma":[0.7401035,0.0001443664,0.2583192,0.00007189462,0.00005413152,0.0001284058,0.00004095307,0.00005837734,0.001079204],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004431911,"threshold_uncertainty_score":0.02343851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05959039912421074,"score_gpt":0.2867051263590897,"score_spread":0.2271147272348789,"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."}}