{"id":"W2059067639","doi":"10.1109/mci.2007.353415","title":"Technology review - Biometrics-Technology, Application, Challenge, and Computational Intelligence Solutions","year":2007,"lang":"en","type":"article","venue":"IEEE Computational Intelligence Magazine","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Biometrics; Computer science; Fingerprint (computing); Fingerprint recognition; Face (sociological concept); Facial recognition system; Artificial intelligence; Computer security; Human–computer interaction; Data science; Pattern recognition (psychology)","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00167869,0.0003303348,0.0003922245,0.00410167,0.0004521188,0.000142939,0.001522705,0.0002768452,0.00004768451],"category_scores_gemma":[0.0004632061,0.0003533082,0.00009345717,0.01489219,0.0007159608,0.0004432819,0.0004241802,0.0004536942,0.0008004333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001605034,"about_ca_system_score_gemma":0.0001817496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007721284,"about_ca_topic_score_gemma":0.00001311536,"domain_scores_codex":[0.9964908,0.00005911355,0.001115728,0.00100294,0.0007389841,0.0005924077],"domain_scores_gemma":[0.9965415,0.0006104673,0.0004090877,0.0006837441,0.001530081,0.0002251226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000003304488,0.0002615552,0.0002003714,0.0001366737,0.00003351984,0.00001054129,0.00006437878,0.004751122,0.00004184787,0.5654093,0.001645741,0.4274416],"study_design_scores_gemma":[0.0001440441,0.0001665067,0.001871428,0.0002419055,0.00003024184,0.0003500224,0.00007785828,0.345357,0.000772335,0.6084964,0.04178858,0.0007037515],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002202372,0.01978875,0.9605489,0.01724944,0.0004381216,0.0005911105,0.00002172381,0.0005606888,0.0005810124],"genre_scores_gemma":[0.7269171,0.004930165,0.2663793,0.001299439,0.00008512007,0.0000887991,0.00009325515,0.00002432542,0.0001824942],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7266968,"threshold_uncertainty_score":0.9999776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.045127048154836,"score_gpt":0.3244289430034975,"score_spread":0.2793018948486615,"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."}}