{"id":"W2138736414","doi":"10.1109/iccitechn.2007.4579428","title":"Iris Recognition: A Java based implementation","year":2007,"lang":"en","type":"article","venue":"","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Iris recognition; Computer vision; Artificial intelligence; IRIS (biosensor); Biometrics; Edge detection; Thresholding; Hamming distance; Blob detection; Canny edge detector; Image (mathematics); Image processing; Algorithm","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":[0.0009801955,0.001177411,0.0009333147,0.001143371,0.000391848,0.001642447,0.00253024,0.0009532334,0.04893582],"category_scores_gemma":[0.002503868,0.0008272002,0.000827335,0.0008080162,0.0003591406,0.001780111,0.001443717,0.001332844,0.03481843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004569026,"about_ca_system_score_gemma":0.0007628618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001560525,"about_ca_topic_score_gemma":0.001365742,"domain_scores_codex":[0.9986901,0.0001270678,0.0001465161,0.0003139757,0.0005224104,0.0001999142],"domain_scores_gemma":[0.9990876,0.000172411,0.0001002977,0.0002308247,0.0003307953,0.00007819061],"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":[0.002822082,0.0008834681,0.004170232,0.001048874,0.0002469714,0.0007618013,0.000282748,0.004952968,0.1098207,0.01387201,0.1498632,0.7112749],"study_design_scores_gemma":[0.001073291,0.0008212085,0.008079888,0.0002711423,0.0002588706,0.002615538,0.000125698,0.2557919,0.2956905,0.01053013,0.4243253,0.0004165891],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008146017,0.000516612,0.6516112,0.0002677244,0.0002823244,0.0007131901,0.002577442,0.3132562,0.02262929],"genre_scores_gemma":[0.1848769,0.001066239,0.6813771,0.001329112,0.0003128524,0.001981223,0.01220371,0.01875513,0.0980978],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04893582,"threshold_uncertainty_score":0.1637066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04862114701705869,"score_gpt":0.3271646328587509,"score_spread":0.2785434858416922,"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."}}