{"id":"W2122132806","doi":"10.1109/ccece.2004.1347697","title":"Automatic fingerprint recognition algorithm","year":2004,"lang":"en","type":"article","venue":"","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Minutiae; Computer science; Preprocessor; Fingerprint (computing); Artificial intelligence; Fingerprint recognition; Pattern recognition (psychology); Algorithm; Simple (philosophy); Feature extraction; Computer vision","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":[0.001015593,0.001142355,0.001381362,0.003029796,0.0008857956,0.001541439,0.001868568,0.001517494,0.01671699],"category_scores_gemma":[0.001989444,0.0003902313,0.001048637,0.002179272,0.0004568314,0.001756638,0.0009139294,0.0009484094,0.01904278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004367241,"about_ca_system_score_gemma":0.0008631176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001066218,"about_ca_topic_score_gemma":0.000799983,"domain_scores_codex":[0.9983743,0.0001532217,0.0001141748,0.0005090851,0.0007255604,0.0001236857],"domain_scores_gemma":[0.9990956,0.0001562171,0.00007019746,0.0002214247,0.0004330326,0.00002364868],"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":[0.000127564,0.00006172884,0.000730208,0.0003095778,0.00004962427,0.0001796682,0.00004784788,0.005644788,0.0323008,0.006005377,0.01968923,0.9348536],"study_design_scores_gemma":[0.0001359462,0.0006127795,0.01066393,0.0003579812,0.0002676661,0.006412419,0.0001424099,0.2735469,0.157257,0.01734941,0.5329255,0.0003280597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005839019,0.002403118,0.9655176,0.0002002937,0.0003892174,0.0004407268,0.001005348,0.009418277,0.01478635],"genre_scores_gemma":[0.07525916,0.002356933,0.8809103,0.0004520669,0.0002298451,0.0005775059,0.003269599,0.0004527033,0.03649195],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01671699,"threshold_uncertainty_score":0.05592388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0262565947131408,"score_gpt":0.2459341513053084,"score_spread":0.2196775565921676,"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."}}