{"id":"W2956084084","doi":"10.1109/pst47121.2019.8949063","title":"Geographical Security Questions for Fallback Authentication","year":2019,"lang":"en","type":"preprint","venue":"","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Usability; Computer science; Computer security; Login; Password; Authentication (law); Session (web analytics); Backup; World Wide Web; Database; Human–computer interaction","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":[0.0005789039,0.0002558416,0.0003350943,0.0002427004,0.0001160483,0.0004825821,0.001733384,0.0003999268,0.00003172151],"category_scores_gemma":[0.00008649633,0.0002449199,0.0003316709,0.0002157639,0.00005014856,0.0002038986,0.0008761787,0.0003792278,0.0003000326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005212321,"about_ca_system_score_gemma":0.0001968719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009516817,"about_ca_topic_score_gemma":0.00004868033,"domain_scores_codex":[0.9978315,0.0001232822,0.0005018909,0.000875584,0.0003606198,0.0003071275],"domain_scores_gemma":[0.9972264,0.0001606765,0.0002278699,0.001860863,0.0003779366,0.0001462942],"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":[0.000004184458,0.0002848484,0.0008749179,0.0004500943,0.00009522059,3.315353e-7,0.01345815,0.000020787,0.00005564781,0.9784076,0.00554871,0.0007994883],"study_design_scores_gemma":[0.0002916941,0.00003803384,0.002096943,0.00009327478,0.00003737495,0.000004054718,0.00003734625,0.7324084,0.00009163558,0.2358014,0.02866791,0.0004319302],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01521272,0.0001859123,0.9699553,0.007100802,0.00270029,0.002059997,0.00005977661,0.0006951557,0.002030005],"genre_scores_gemma":[0.9883984,0.00003218128,0.009017497,0.0003462366,0.000136122,0.0003544232,0.0001368344,0.0000178663,0.001560482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9731857,"threshold_uncertainty_score":0.9987543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02274878660658229,"score_gpt":0.2873533479839063,"score_spread":0.264604561377324,"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."}}