{"id":"W2073654225","doi":"10.5430/air.v4n1p1","title":"Using a predefined passphrase to evaluate a speaker verification system","year":2014,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Speaker verification; Computer science; Biometrics; Variety (cybernetics); Process (computing); Feature (linguistics); Speaker recognition; Focus (optics); Speech recognition; Artificial intelligence; Natural language processing; Programming language; Linguistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005194723,0.0001702867,0.0002421302,0.0006320496,0.0004119066,0.000425825,0.00149351,0.00008716393,0.00003107196],"category_scores_gemma":[0.001146764,0.0001626714,0.00008775863,0.002702571,0.0001229899,0.0004673873,0.000514442,0.0003080328,0.001121125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003913663,"about_ca_system_score_gemma":0.0001365434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003777055,"about_ca_topic_score_gemma":0.0001015607,"domain_scores_codex":[0.9959285,0.0007634371,0.000540089,0.0008112681,0.001234019,0.0007226685],"domain_scores_gemma":[0.9969169,0.0003910734,0.0000917971,0.001431395,0.0009027053,0.0002661318],"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":[0.00002969708,0.00008753379,0.00007464686,0.00002659799,0.00001542639,0.000007293686,0.0007207774,0.004441837,0.08555941,0.5798951,0.0001470632,0.3289946],"study_design_scores_gemma":[0.00001207005,0.0001305277,0.0000270601,0.00006317164,0.000005765399,0.000006252005,0.0002147503,0.7486022,0.1959448,0.05387609,0.0009396788,0.0001776739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0408391,0.00001953581,0.9554945,0.0007602272,0.0001016953,0.0005228595,9.741013e-7,0.0003790181,0.001882048],"genre_scores_gemma":[0.8530011,0.000004097932,0.1466629,0.00004677349,0.0001006753,0.0000926092,0.000001545586,0.0000173734,0.00007294782],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8121619,"threshold_uncertainty_score":0.9996566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3227113673669672,"score_gpt":0.4872202259271605,"score_spread":0.1645088585601934,"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."}}