{"id":"W3143652836","doi":"10.1109/ultsym.2009.5441399","title":"High resolution ultrasonic method for 3D fingerprint recognizable characteristics in biometrics identification","year":2009,"lang":"en","type":"article","venue":"","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Biometrics; Fingerprint (computing); Identification (biology); Computer science; Artificial intelligence; Visualization; Computer vision; Fingerprint recognition; Ultrasonic sensor; Crime scene; Usability; Pattern recognition (psychology); Human–computer interaction; Geography; Acoustics","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":[0.0006077926,0.0005293435,0.0005140014,0.001589034,0.0002718577,0.0008793448,0.0008550346,0.00137353,0.00447828],"category_scores_gemma":[0.001145284,0.0003553549,0.0004919481,0.001495962,0.000407624,0.001061517,0.0007092864,0.0008082522,0.002634119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003029754,"about_ca_system_score_gemma":0.0003483063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000626455,"about_ca_topic_score_gemma":0.0006238323,"domain_scores_codex":[0.9987431,0.000257457,0.00005824516,0.0002640981,0.0005952166,0.00008195614],"domain_scores_gemma":[0.9994687,0.0001594346,0.00007036929,0.000105006,0.0001768549,0.00001959758],"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":[0.0001801129,0.00009016742,0.001973955,0.0006457632,0.0000352286,0.0004374437,0.000354613,0.004311556,0.3879248,0.008312853,0.005158497,0.590575],"study_design_scores_gemma":[0.00005908454,0.0009005125,0.01373768,0.0003430587,0.0001960557,0.009655756,0.0006058219,0.1698741,0.6413262,0.006722383,0.156209,0.0003704198],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01830795,0.005007556,0.9662832,0.0003118902,0.0003126774,0.0001259605,0.000249247,0.001392254,0.00800926],"genre_scores_gemma":[0.2607475,0.005552751,0.7165285,0.000395634,0.000305447,0.0003629877,0.0004048044,0.0001712615,0.0155311],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00447828,"threshold_uncertainty_score":0.01498133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0302804846346709,"score_gpt":0.300721366483908,"score_spread":0.270440881849237,"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."}}