{"id":"W2618393310","doi":"10.1007/978-3-319-59063-9_60","title":"An Evaluation of Fuzzy Measure for Face Recognition","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Measure (data warehouse); Face (sociological concept); Facial recognition system; Fuzzy logic; Artificial intelligence; Pattern recognition (psychology); Data mining","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":[0.003542175,0.0006148897,0.00111208,0.002740418,0.0005691029,0.001674912,0.001209317,0.001007231,0.002457123],"category_scores_gemma":[0.007598696,0.0001697353,0.0008606202,0.001473346,0.0007208964,0.001510105,0.000859588,0.0005320361,0.0003914711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001812064,"about_ca_system_score_gemma":0.0006051712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001897503,"about_ca_topic_score_gemma":0.0014306,"domain_scores_codex":[0.9961061,0.000863665,0.0001886851,0.0003596497,0.00232574,0.0001561405],"domain_scores_gemma":[0.9960876,0.001836023,0.0001402759,0.0002873634,0.001537282,0.0001116282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009227015,0.0001829349,0.003602535,0.0006108688,0.0001933499,0.0001238585,0.0002407481,0.04543746,0.05126575,0.06591258,0.004251768,0.8272555],"study_design_scores_gemma":[0.00002932932,0.001088783,0.007404335,0.00009428003,0.0001679116,0.0004900313,0.000160774,0.9220406,0.03480818,0.02714694,0.006486471,0.00008250374],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06961083,0.005060709,0.9142105,0.000188517,0.0003024336,0.0001172319,0.0001894889,0.0004173322,0.009902899],"genre_scores_gemma":[0.6686949,0.001157779,0.3256486,0.00007291638,0.0001766975,0.0001102808,0.0003521139,0.00008129043,0.003705465],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003542175,"threshold_uncertainty_score":0.01873302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07926603880853486,"score_gpt":0.3165934306683353,"score_spread":0.2373273918598004,"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."}}