{"id":"W4385611907","doi":"10.5121/csit.2023.131206","title":"Authentication Technique based on Image Recognition: Example of Quantitative Evaluation by Probabilistic Model Checker","year":2023,"lang":"en","type":"article","venue":"","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Probabilistic logic; Computer science; Relation (database); Authentication (law); Probabilistic CTL; Identification (biology); Process (computing); Image (mathematics); Statistical model; Model checking; Artificial intelligence; Data mining; Machine learning; Theoretical computer science; Pattern recognition (psychology); Computer vision; Probabilistic analysis of algorithms; Programming language; Computer security","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":[0.001295083,0.00007884468,0.00008255775,0.000160559,0.00006493734,0.00004680562,0.0001903964,0.00005234082,0.00004393111],"category_scores_gemma":[0.0003029033,0.00007352474,0.00003621308,0.0006822122,0.0000313608,0.0003048435,0.00002657091,0.00006464359,0.00009848727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005708372,"about_ca_system_score_gemma":0.00007626852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007382849,"about_ca_topic_score_gemma":0.000005651637,"domain_scores_codex":[0.9989127,0.0001192598,0.0001887774,0.0002920224,0.0003792192,0.0001080201],"domain_scores_gemma":[0.9990989,0.0001247383,0.00009692535,0.0003374261,0.0003132063,0.00002880704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001501533,0.0008953345,0.00006824645,0.0002907979,0.00004385981,0.00000166119,0.00435411,0.047945,0.7198909,0.1389955,0.02834885,0.05901556],"study_design_scores_gemma":[0.0001550475,0.0001279383,0.0001981541,0.00002361145,0.000008441126,3.010296e-7,0.00001168921,0.8722757,0.08342859,0.04367048,0.00002073893,0.00007938014],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01774035,0.000002589369,0.978782,0.0003260727,0.00007624283,0.0005970819,0.000009638576,0.0002974615,0.002168555],"genre_scores_gemma":[0.8426847,0.000001382043,0.1566205,0.00007744755,0.000009055314,0.0003646509,0.00009027214,0.000008606004,0.0001434012],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8249443,"threshold_uncertainty_score":0.2998252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1067840418036325,"score_gpt":0.3248503020525072,"score_spread":0.2180662602488747,"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."}}