{"id":"W2155628890","doi":"10.1109/ccece.2006.277447","title":"Towards a Measure of Biometric Information","year":2006,"lang":"en","type":"article","venue":"","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Biometrics; Entropy (arrow of time); Pattern recognition (psychology); Computer science; Artificial intelligence; Population; Feature (linguistics); Measure (data warehouse); Kullback–Leibler divergence; Facial recognition system; Gaussian; Information theory; Face (sociological concept); Mathematics; Data mining; Statistics","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":[0.01075222,0.001183306,0.001718962,0.005992823,0.001223019,0.007311792,0.002616252,0.003686317,0.002355345],"category_scores_gemma":[0.03700466,0.0008803923,0.001215946,0.003610513,0.009663564,0.01146647,0.005291938,0.004804503,0.00203051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002669959,"about_ca_system_score_gemma":0.001188711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000674644,"about_ca_topic_score_gemma":0.0002596549,"domain_scores_codex":[0.987905,0.003946017,0.0007754439,0.002571493,0.004543766,0.0002581693],"domain_scores_gemma":[0.9828825,0.007431138,0.001606298,0.003643827,0.003942006,0.0004942744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003361988,0.00003547243,0.000942592,0.0001711894,0.00004860915,0.0000593817,0.0002895431,0.006664304,0.003742212,0.9371948,0.001583153,0.04923488],"study_design_scores_gemma":[0.0000135523,0.0001451318,0.001585672,0.0002390182,0.00003277156,0.0004068282,0.0002375701,0.06335746,0.003443448,0.8919474,0.0384794,0.000111791],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006164246,0.0023732,0.9783336,0.0018068,0.0003474515,0.00004061076,0.00009326309,0.0001649107,0.01067587],"genre_scores_gemma":[0.1909459,0.003799018,0.7954456,0.001291507,0.001379856,0.0003071716,0.0003434629,0.0002302521,0.006257361],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01075222,"threshold_uncertainty_score":0.05686384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01266741953714987,"score_gpt":0.2174794084622204,"score_spread":0.2048119889250706,"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."}}