{"id":"W1998131232","doi":"10.1109/roman.2014.6926273","title":"Multimodal biometric identification system for mobile robots combining human metrology to face recognition and speaker identification","year":2014,"lang":"en","type":"article","venue":"","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"Biometrics; Computer science; Identification (biology); Modality (human–computer interaction); Artificial intelligence; Computer vision; Face (sociological concept); Modalities; Facial recognition system; Pattern recognition (psychology); Robot; Speech recognition","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":[],"consensus_categories":[],"category_scores_codex":[0.0020712,0.0001759189,0.0002544835,0.00206359,0.0003962709,0.0006100793,0.0006002579,0.0001458101,0.00001062057],"category_scores_gemma":[0.0003181353,0.0001813758,0.00007287406,0.003148397,0.00004807252,0.0005888757,0.0001493832,0.00008581456,0.0003069961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001168198,"about_ca_system_score_gemma":0.00001559091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001038234,"about_ca_topic_score_gemma":0.00001798572,"domain_scores_codex":[0.9976861,0.00018931,0.0006784779,0.0008252242,0.000315709,0.000305208],"domain_scores_gemma":[0.9981321,0.0002640814,0.0003168382,0.0006708196,0.0004384929,0.0001777471],"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":[0.00003238728,0.0005381047,0.001054615,0.0004350607,0.0001000746,9.368816e-7,0.002316754,0.0002158854,0.3188027,0.08782911,0.002568895,0.5861055],"study_design_scores_gemma":[0.004400375,0.001013258,0.1427829,0.00007933694,0.0001550364,0.00006354225,0.001531746,0.643022,0.1837677,0.007279252,0.01412688,0.001777949],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.178615,0.0000478051,0.8189881,0.0002847671,0.0006802599,0.0009095008,0.00001752564,0.0002911248,0.0001659147],"genre_scores_gemma":[0.9753628,0.000004166935,0.02343948,0.000122924,0.00006269938,0.0003538066,0.0001604452,0.00001476512,0.0004789227],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7967478,"threshold_uncertainty_score":0.7396292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04209890750620349,"score_gpt":0.2911656486731221,"score_spread":0.2490667411669186,"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."}}