{"id":"W2165249306","doi":"10.1109/mwscas.2013.6674895","title":"Enhancement of low-quality fingerprint images by a three-stage filtering scheme","year":2013,"lang":"en","type":"article","venue":"","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Fingerprint (computing); Artificial intelligence; Computer vision; Ridge; Computer science; Filter (signal processing); Fingerprint recognition; Orientation (vector space); Compensation (psychology); Pattern recognition (psychology); Image quality; Stage (stratigraphy); Image (mathematics); Mathematics; Geology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003704875,0.0000839174,0.0001282423,0.0001077604,0.0000465953,0.0001476922,0.0006050165,0.00003499187,0.001183815],"category_scores_gemma":[0.00005141104,0.00007334937,0.00005118875,0.0004740218,0.00004442641,0.0003631423,0.0003071279,0.00006257421,0.0002175931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002693059,"about_ca_system_score_gemma":0.00002108418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006297175,"about_ca_topic_score_gemma":0.000007949142,"domain_scores_codex":[0.998917,0.00003081949,0.0003278634,0.0002753406,0.0002766737,0.0001723351],"domain_scores_gemma":[0.9990676,0.0000483532,0.0001255992,0.0005598667,0.0001306678,0.00006791008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000001543657,0.0002947491,0.0009927488,0.0001202903,0.00002049908,4.50911e-7,0.0003000722,7.187053e-7,0.9148617,0.02681896,0.01178607,0.04480224],"study_design_scores_gemma":[0.0002040433,0.00002557664,0.01268656,0.00001342145,8.949115e-7,3.411612e-7,0.00003149336,0.01363101,0.9679461,0.0008546915,0.004420293,0.0001855605],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1642916,0.00007571762,0.8320394,0.0006438153,0.0001125272,0.0001490241,0.000004286522,0.00006542575,0.002618176],"genre_scores_gemma":[0.92016,0.00001634381,0.07652409,0.0002007724,0.000008028481,0.00002639284,0.000003515854,0.000003049435,0.003057807],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7558684,"threshold_uncertainty_score":0.9997292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02678706904824827,"score_gpt":0.2814084847744591,"score_spread":0.2546214157262108,"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."}}