{"id":"W2029711940","doi":"10.1109/cw.2014.45","title":"Multimodal Biometrics Using Cancelable Feature Fusion","year":2014,"lang":"en","type":"article","venue":"","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Biometrics; Computer science; Feature (linguistics); Template; Fusion; Pattern recognition (psychology); Authentication (law); Artificial intelligence; Feature extraction; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008257842,0.0008621748,0.0009877717,0.0009915478,0.0004990715,0.001030596,0.001025904,0.001105507,0.003442346],"category_scores_gemma":[0.001887426,0.0003123802,0.001238027,0.0009402605,0.0005415907,0.001929612,0.00157454,0.0007655494,0.001746716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006038722,"about_ca_system_score_gemma":0.0004137481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001170304,"about_ca_topic_score_gemma":0.0008171487,"domain_scores_codex":[0.998149,0.0002643637,0.0001053024,0.0004265082,0.0009177283,0.0001370363],"domain_scores_gemma":[0.9994088,0.00009673279,0.000073225,0.0001595437,0.0002393532,0.00002231931],"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":[0.0007099958,0.0001083055,0.001259259,0.0002495224,0.0002157934,0.0005080355,0.0001784223,0.03076206,0.3251801,0.02166161,0.004265327,0.6149016],"study_design_scores_gemma":[0.00004930322,0.000734605,0.003289763,0.0000639842,0.0002825945,0.00239991,0.00008924034,0.6692787,0.2719134,0.01979297,0.03189612,0.0002092444],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01385017,0.0005315242,0.9805936,0.0001425781,0.0001375766,0.00006336805,0.0001063221,0.00122302,0.003351898],"genre_scores_gemma":[0.5837555,0.0009331018,0.4028211,0.0004449108,0.0001766245,0.0001528457,0.0005835845,0.0001765971,0.01095577],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003442346,"threshold_uncertainty_score":0.0115158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0259190973195131,"score_gpt":0.2663342569666038,"score_spread":0.2404151596470907,"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."}}