{"id":"W2130562169","doi":"10.1109/icimp.2009.23","title":"Cognitive-Based Biometrics System for Static User Authentication","year":2009,"lang":"en","type":"article","venue":"","topic":"User Authentication and Security Systems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Biometrics; Computer science; Authentication (law); Software deployment; The Internet; Computer security; Multi-factor authentication; Human–computer interaction; Authentication protocol; World Wide Web; Software engineering","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":[0.0005881141,0.000288188,0.0004916548,0.0006230744,0.0003169907,0.0003656405,0.0005824485,0.0005331562,0.003978701],"category_scores_gemma":[0.001137969,0.0001002137,0.0002707364,0.0004085836,0.0002403248,0.0005806795,0.0004507655,0.0003326861,0.001862663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003078267,"about_ca_system_score_gemma":0.0003723971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008978017,"about_ca_topic_score_gemma":0.001232663,"domain_scores_codex":[0.9995713,0.00007420846,0.00002291385,0.00009221082,0.0001938257,0.00004550423],"domain_scores_gemma":[0.9996607,0.00006321668,0.00004866054,0.0000574508,0.0001413288,0.00002859864],"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":[0.001647095,0.0005176692,0.01061371,0.000272863,0.00008594757,0.0004464212,0.0002877946,0.002840699,0.3867577,0.004282137,0.004065025,0.5881829],"study_design_scores_gemma":[0.0003018652,0.004284573,0.1078691,0.0001392124,0.0004434205,0.008109245,0.0003132165,0.3912171,0.4462236,0.004697377,0.03608396,0.0003173051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.485148,0.001232121,0.4939764,0.0004739229,0.0003789118,0.00036743,0.0004648956,0.005134778,0.01282347],"genre_scores_gemma":[0.952427,0.0002195757,0.04151858,0.0001408828,0.00003942629,0.00008433014,0.000130197,0.0000166983,0.005423375],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003978701,"threshold_uncertainty_score":0.01331007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03293521815334764,"score_gpt":0.2923740759621488,"score_spread":0.2594388578088012,"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."}}