{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007632521,0.0005970553,0.0003628422,0.0005412502,0.001219589,0.001780023,0.0007645276,0.0009797441,0.01206402],"category_scores_gemma":[0.06024612,0.0003702381,0.0003906759,0.0002758768,0.002058324,0.00417706,0.00282693,0.001100171,0.001924503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007718855,"about_ca_system_score_gemma":0.0009844721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000579407,"about_ca_topic_score_gemma":0.0006008704,"domain_scores_codex":[0.990456,0.007250685,0.0005229544,0.0005752486,0.0009481568,0.0002469479],"domain_scores_gemma":[0.9416457,0.0422291,0.003777596,0.006286734,0.004643742,0.001416934],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0041188,0.003402734,0.126634,0.003908444,0.00009475476,0.0009124873,0.1010056,0.002688827,0.08357901,0.06893387,0.02248047,0.5822411],"study_design_scores_gemma":[0.001469772,0.01811654,0.3264498,0.002314372,0.0004105226,0.007029067,0.06187904,0.04428766,0.07803049,0.1170946,0.342136,0.0007820752],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8557665,0.000484631,0.1101897,0.002887471,0.0001470261,0.002871988,0.0002829258,0.0018217,0.02554809],"genre_scores_gemma":[0.9487277,0.000132917,0.04675269,0.0006346992,0.00002584669,0.001236426,0.0001860887,0.000104863,0.002198559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01206402,"threshold_uncertainty_score":0.0403651,"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."}}