{"id":"W2500190401","doi":"10.1007/978-3-319-39378-0_50","title":"Linguistic Descriptors and Analytic Hierarchy Process in Face Recognition Realized by Humans","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Voting; Identification (biology); Facial recognition system; Analytic hierarchy process; Artificial intelligence; Face (sociological concept); Process (computing); Suspect; Hierarchy; Machine learning; Parametric statistics; Natural language processing; Pattern recognition (psychology); Linguistics; Operations research; Mathematics; Statistics","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"],"consensus_categories":[],"category_scores_codex":[0.0006803131,0.0004395399,0.0004893379,0.0009818175,0.0001911834,0.000393151,0.001167418,0.0003080647,0.00002448367],"category_scores_gemma":[0.0002362217,0.0003612508,0.00006532123,0.0005063032,0.0004894444,0.000608725,0.0004269017,0.0005645864,0.00003655851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001976606,"about_ca_system_score_gemma":0.0002503816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002418605,"about_ca_topic_score_gemma":0.00006492957,"domain_scores_codex":[0.9967048,0.00005586897,0.0005328312,0.00146726,0.0006683767,0.0005709293],"domain_scores_gemma":[0.9983881,0.0003482702,0.0002555416,0.0005983096,0.0002303359,0.0001794304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002772713,0.0000589763,0.0001712434,0.000157911,0.00001093609,0.0001186447,0.004074058,0.0005717468,0.0009238336,0.001013744,0.0001017955,0.9927694],"study_design_scores_gemma":[0.001701743,0.0003952087,0.0001448856,0.005011928,0.00002480841,0.00008542051,0.000002348378,0.1897255,0.006000821,0.7930186,0.002045385,0.001843337],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002507328,0.0004900706,0.9923497,0.0004975269,0.0007518494,0.000426863,0.0000212222,0.0001185652,0.002836886],"genre_scores_gemma":[0.897546,0.000645039,0.09762537,0.002282767,0.0005374343,0.00006986916,0.0000584955,0.00008851453,0.001146529],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.990926,"threshold_uncertainty_score":0.9998839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02179805180015682,"score_gpt":0.2619041789382045,"score_spread":0.2401061271380477,"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."}}