{"id":"W2905558153","doi":"10.1364/ao.57.010305","title":"Double random phase encoding for cancelable face and iris recognition","year":2018,"lang":"en","type":"article","venue":"Applied Optics","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Biometrics; Computer science; Iris recognition; Artificial intelligence; Encryption; Face (sociological concept); Feature (linguistics); Pattern recognition (psychology); IRIS (biosensor); Encoding (memory); Feature extraction; Computer vision; Computer security","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":[],"consensus_categories":[],"category_scores_codex":[0.0003105212,0.00006922418,0.00009682506,0.0001041575,0.0001979428,0.000184178,0.0001962359,0.00005316772,0.00001124293],"category_scores_gemma":[0.00002020904,0.00006909008,0.00001852301,0.000434806,0.0000587064,0.0001443903,0.00005733636,0.00004635811,0.00004521979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000210673,"about_ca_system_score_gemma":0.00002867234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000153649,"about_ca_topic_score_gemma":0.000006186479,"domain_scores_codex":[0.9993465,0.00000587153,0.0001414943,0.0002421511,0.0001041728,0.000159839],"domain_scores_gemma":[0.9994772,0.00007864919,0.0000656948,0.000204734,0.0001116738,0.00006206633],"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":[0.0006933779,0.0005455179,0.00003232007,0.0001644468,0.00008816073,0.00000222519,0.00776045,0.000007874428,0.06548555,0.3254184,0.0203073,0.5794944],"study_design_scores_gemma":[0.03959021,0.0004619268,0.00006880848,0.00003216898,0.0000857882,0.00001826043,0.0005279216,0.2234756,0.3880464,0.03813697,0.3085423,0.001013716],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03292259,0.00006566483,0.9583463,0.0002735198,0.0003203219,0.0004158997,0.00001200411,0.0000826743,0.007561038],"genre_scores_gemma":[0.8727417,0.00007090705,0.1263099,0.0002497525,0.0001322364,0.00007484551,0.00001992663,0.000006531182,0.0003941792],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8398191,"threshold_uncertainty_score":0.2817412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05569695132514568,"score_gpt":0.3038091403995686,"score_spread":0.248112189074423,"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."}}