{"id":"W2037193857","doi":"10.1145/1993060.1993062","title":"Homogeneous physio-behavioral visual and mouse-based biometric","year":2011,"lang":"en","type":"article","venue":"ACM Transactions on Computer-Human Interaction","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Biometrics; Computer science; Password; Word error rate; Artificial intelligence; Keystroke dynamics; Homogeneous; Classifier (UML); Pattern recognition (psychology); Computer vision; Machine learning; Data mining; Computer security; 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":[0.0005866141,0.0004573347,0.000788178,0.0008728877,0.000196726,0.0006236605,0.0007214647,0.0005622175,0.002353282],"category_scores_gemma":[0.00168923,0.0001857627,0.0004527507,0.000665317,0.0003383546,0.001279804,0.0007359897,0.0003196226,0.001764694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000184998,"about_ca_system_score_gemma":0.0002478448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002956238,"about_ca_topic_score_gemma":0.0004325342,"domain_scores_codex":[0.9990662,0.0001402191,0.00005478414,0.0002566243,0.0004185333,0.00006371973],"domain_scores_gemma":[0.998931,0.0002166309,0.0002440504,0.0002201061,0.0003124099,0.00007594523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008998741,0.0002830098,0.01050036,0.0005049247,0.0001152405,0.0003129676,0.0001369844,0.003391513,0.5818068,0.003099591,0.001136152,0.3978125],"study_design_scores_gemma":[0.0001478861,0.006895443,0.1635408,0.0002227093,0.0006081501,0.01566951,0.0002662988,0.2871309,0.4803166,0.00530469,0.03946614,0.0004309598],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2083102,0.002635746,0.7777007,0.0002028071,0.0003008447,0.0002437448,0.0003681094,0.002946816,0.007290933],"genre_scores_gemma":[0.9030142,0.0007682356,0.08841038,0.0002203014,0.0001506052,0.0001340106,0.0002465048,0.00005822239,0.006997504],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002353282,"threshold_uncertainty_score":0.007872522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0657925871163838,"score_gpt":0.3125464353237824,"score_spread":0.2467538482073986,"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."}}