{"id":"W4225166714","doi":"10.18280/ijsse.120214","title":"Face Recognition System for Control Access to Restrictive Domain","year":2022,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Face recognition and analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Facial recognition system; Artificial intelligence; Computer science; Feature extraction; Pattern recognition (psychology); Three-dimensional face recognition; Support vector machine; Face (sociological concept); Face detection; Feature (linguistics); Process (computing); Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004546323,0.00006690651,0.0001399214,0.0002916947,0.00008758491,0.0001304396,0.0004857636,0.00001697326,0.000008670574],"category_scores_gemma":[0.00006635072,0.00006856036,0.00009201149,0.0001759299,0.000004041056,0.0004304361,0.0001266411,0.0001392726,0.000001044624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001597048,"about_ca_system_score_gemma":0.00002785456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004704754,"about_ca_topic_score_gemma":0.000001047539,"domain_scores_codex":[0.999176,0.00003388557,0.0002786127,0.0001081192,0.0003104298,0.00009292459],"domain_scores_gemma":[0.9993218,0.0001431617,0.000138486,0.00004900914,0.0002664473,0.00008114789],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001644654,0.0003121778,0.0002985781,0.0001618286,0.001779696,0.0003222593,0.008522069,0.7982971,0.003952348,0.04038468,0.001043171,0.1432814],"study_design_scores_gemma":[0.005212982,0.0005026774,0.001325031,0.0002785002,0.00007616998,0.001053891,0.002143822,0.9404542,0.002151918,0.004786714,0.04150445,0.0005096491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0202665,0.00007800282,0.9752095,0.003413063,0.0007409586,0.0001065075,0.00009428409,0.00002330068,0.00006788637],"genre_scores_gemma":[0.9948496,0.00003143072,0.004745064,0.000224118,0.0001232474,0.0000121344,0.000005498541,0.000004354826,0.000004594858],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.974583,"threshold_uncertainty_score":0.279581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0108910973149947,"score_gpt":0.2410917923026326,"score_spread":0.2302006949876379,"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."}}