{"id":"W4395660503","doi":"10.46254/ba06.20230105","title":"Computer Vision Based Automated Attendance System Using Face Recognition","year":2023,"lang":"en","type":"article","venue":"","topic":"Face recognition and analysis","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Facial recognition system; Computer science; Computer vision; Artificial intelligence; Face (sociological concept); Face detection; Attendance; 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":[0.0002874463,0.0001273173,0.0001680814,0.0003080284,0.000171427,0.0002241863,0.0002897154,0.00005997656,0.00004013072],"category_scores_gemma":[0.000008149616,0.0001130992,0.000104818,0.001593623,0.00001759418,0.0004116007,0.0001084619,0.00006575212,0.002172819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006795795,"about_ca_system_score_gemma":0.0000354701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003300337,"about_ca_topic_score_gemma":0.000004883128,"domain_scores_codex":[0.9987314,0.000109685,0.0002344086,0.0003899816,0.000278751,0.0002557829],"domain_scores_gemma":[0.9993374,0.00007228613,0.00008024492,0.0002883427,0.0001305611,0.00009112828],"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":[0.00003105608,0.0003928539,0.0007416975,0.0009021423,0.0002678217,0.0005420872,0.0005899636,0.1815757,0.05010272,0.002831449,0.05222964,0.7097929],"study_design_scores_gemma":[0.0002433038,0.00002770685,0.000428117,0.0001433173,0.000009804627,0.00001228408,0.00004728656,0.9963251,0.002404306,0.00002345012,0.0001657784,0.0001695766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05228363,0.000005256334,0.9407914,0.0007392209,0.0003224809,0.0001074604,0.000007150653,0.005272272,0.0004710822],"genre_scores_gemma":[0.8671833,0.000002496216,0.1319764,0.0005232013,0.00005383523,0.000007194947,0.00005412016,0.00001271731,0.0001866767],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8148997,"threshold_uncertainty_score":0.9986041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03907385321158705,"score_gpt":0.2860088335270875,"score_spread":0.2469349803155005,"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."}}