{"id":"W4280517983","doi":"10.3390/s22103620","title":"RETRACTED: Match-Level Fusion of Finger-Knuckle Print and Iris for Human Identity Validation Using Neuro-Fuzzy Classifier","year":2022,"lang":"en","type":"article","venue":"Sensors","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":19,"is_retracted":true,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"Qassim University","keywords":"Biometrics; Artificial intelligence; Iris recognition; Pattern recognition (psychology); Computer science; Classifier (UML); Feature extraction; Fuzzy logic; Artificial neural network; Computer vision","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":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001228768,0.0005750454,0.0007812611,0.000596214,0.0008044955,0.0009762806,0.001752634,0.001701339,0.009877411],"category_scores_gemma":[0.002552757,0.0001856851,0.0006820237,0.0003498242,0.0003620882,0.000987392,0.0007190768,0.001091093,0.004409025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006646715,"about_ca_system_score_gemma":0.001016004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01411792,"about_ca_topic_score_gemma":0.009038012,"domain_scores_codex":[0.9991198,0.0000811553,0.00007282204,0.0002112794,0.0004298326,0.00008507931],"domain_scores_gemma":[0.9986577,0.0001307509,0.00002685683,0.0001610279,0.0009683619,0.0000552358],"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":[0.001505699,0.0003878817,0.007614161,0.0005294202,0.0002345247,0.001448498,0.0003703573,0.04029977,0.0905598,0.004674434,0.0719569,0.7804185],"study_design_scores_gemma":[0.00005612864,0.0003725198,0.008067266,0.00009805687,0.000107662,0.0009975276,0.0002455572,0.8251897,0.1204264,0.001950019,0.04240518,0.00008389921],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1750081,0.002858912,0.762137,0.003462182,0.006454843,0.0008562501,0.001807781,0.0128759,0.03453896],"genre_scores_gemma":[0.72832,0.0008013166,0.1981558,0.0007755443,0.0003999522,0.0001875307,0.003249082,0.0003854333,0.06772526],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9982986,"threshold_uncertainty_score":0.03304327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1044655196166121,"score_gpt":0.3190579954491928,"score_spread":0.2145924758325806,"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."}}