{"id":"W173890511","doi":"10.1007/978-1-4020-8823-0_39","title":"High Resolution Ultrasonic Method for 3D Fingerprint Representation in Biometrics","year":2008,"lang":"en","type":"book-chapter","venue":"Acoustical imaging","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Biometrics; Fingerprint (computing); Artificial intelligence; Identification (biology); Ultrasonic sensor; Computer science; Computer vision; Pattern recognition (psychology); Feature (linguistics); Acoustics; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008727265,0.0002567915,0.0003733631,0.002145669,0.0001434076,0.0002015466,0.000659141,0.0002376495,0.00003330177],"category_scores_gemma":[0.00127164,0.0002802635,0.0001526311,0.001131659,0.0001009377,0.0003185323,0.0002207158,0.0004267425,0.00005862247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003668467,"about_ca_system_score_gemma":0.0001274253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001302812,"about_ca_topic_score_gemma":0.000004857197,"domain_scores_codex":[0.9975382,0.00006165467,0.0006189778,0.0008815796,0.0005186751,0.0003808867],"domain_scores_gemma":[0.9973171,0.001317952,0.0002524123,0.0007003437,0.0002940955,0.0001180978],"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":[0.00001939857,0.000115281,0.00004447785,0.0001113682,0.00004105685,0.00007603759,0.000277215,0.0003220389,0.0007592404,0.2400755,0.01389738,0.744261],"study_design_scores_gemma":[0.0005444023,0.0000281891,0.0007618638,0.00008426181,0.00004526252,0.00006427836,0.000007094536,0.9004937,0.0002493347,0.02719619,0.0699961,0.0005293171],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000004764536,0.0006746296,0.9899591,0.001096588,0.0008130163,0.0004203924,0.00002940424,0.0001524714,0.006849594],"genre_scores_gemma":[0.007266441,0.0006328146,0.9775189,0.0003961593,0.0002031459,0.00003886654,0.000113127,0.00003977478,0.01379077],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9001716,"threshold_uncertainty_score":0.999965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04273159744232875,"score_gpt":0.3173593112745971,"score_spread":0.2746277138322684,"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."}}