{"id":"W2897592681","doi":"10.1145/3234695.3241032","title":"Bend Passwords on BendyPass","year":2018,"lang":"en","type":"article","venue":"","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Password; Gesture; Computer science; Authentication (law); Computer security; Cognitive password; Human–computer interaction; Haptic technology; Password strength; Artificial intelligence; One-time password","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004822573,0.0008104387,0.0005215207,0.0006230524,0.0004516594,0.000758072,0.0006068858,0.0008095348,0.04171705],"category_scores_gemma":[0.003092735,0.0003594547,0.0003950621,0.0004165922,0.0005425164,0.002869807,0.002853259,0.0005587946,0.008887066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002011825,"about_ca_system_score_gemma":0.0001998076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003729568,"about_ca_topic_score_gemma":0.0005068673,"domain_scores_codex":[0.9991702,0.0001239664,0.0000797551,0.0001251432,0.0003762286,0.0001246667],"domain_scores_gemma":[0.9976331,0.0005694786,0.0003075385,0.0007849468,0.0003970231,0.0003079098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.005881144,0.0003447589,0.01349897,0.00146004,0.00005908285,0.0049362,0.00282704,0.001126991,0.3139212,0.01401415,0.04510744,0.596823],"study_design_scores_gemma":[0.0003603921,0.006517536,0.07464888,0.0009890676,0.000168498,0.0220073,0.00243939,0.0166679,0.4211107,0.007656671,0.4469587,0.0004748976],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.6337918,0.003172358,0.2464849,0.001572896,0.001544167,0.001221746,0.00263667,0.02685842,0.08271696],"genre_scores_gemma":[0.8937344,0.0008786232,0.04556778,0.0005098669,0.00009741258,0.0001859436,0.000918983,0.0007321456,0.05737477],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04171705,"threshold_uncertainty_score":0.1395574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01641311364270437,"score_gpt":0.2568546539305878,"score_spread":0.2404415402878834,"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."}}