{"id":"W3016704080","doi":"10.1109/icces48960.2019.9068130","title":"Parallel Computer For Face Recognition Using Artificial Intelligence","year":2019,"lang":"en","type":"article","venue":"","topic":"Face recognition and analysis","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Facial recognition system; Task (project management); Face (sociological concept); Parallelism (grammar); Artificial intelligence; Identity (music); Task parallelism; Artificial neural network; Scale (ratio); Parallel computing; Machine learning; Pattern recognition (psychology)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001670353,0.00009367493,0.0001317604,0.0001007874,0.00006897943,0.0001645822,0.0002664198,0.00004643097,0.000216699],"category_scores_gemma":[0.000009016954,0.00008462644,0.0001170004,0.0002616705,0.00001344969,0.0003638027,0.00006930457,0.00005160644,0.0009703123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002083848,"about_ca_system_score_gemma":0.00002465372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001307305,"about_ca_topic_score_gemma":0.000006569356,"domain_scores_codex":[0.9991333,0.00002682169,0.0002058176,0.0003131214,0.0001271267,0.0001938068],"domain_scores_gemma":[0.9994838,0.00008057642,0.00005870389,0.0002053663,0.000114425,0.00005708926],"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":[0.000009386283,0.00008510135,0.00003576077,0.00002178501,0.0000335027,0.000001006698,0.0001764477,0.008114801,0.001162806,0.03003938,0.0001525832,0.9601675],"study_design_scores_gemma":[0.00005822195,0.00004934169,0.00001114604,0.00001350519,0.000007468238,0.000003827691,0.00006228848,0.9704068,0.004427497,0.02449312,0.0003161517,0.0001505904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01582669,0.000007258838,0.982272,0.0005184749,0.0003063281,0.0002245679,0.000003401648,0.0001129571,0.0007282941],"genre_scores_gemma":[0.2678898,0.000005217142,0.731128,0.0006845504,0.00008007026,0.000008366552,0.00001264562,0.000006063824,0.0001853133],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.962292,"threshold_uncertainty_score":0.9998075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09533670367019402,"score_gpt":0.2996570777242966,"score_spread":0.2043203740541025,"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."}}