{"id":"W4413226860","doi":"10.18280/isi.300617","title":"Class Attendance System Using Facial Recognition","year":2025,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Covenant University Centre for Research, Innovation and Discovery; Covenant University","keywords":"Class (philosophy); Attendance; Artificial intelligence; Computer science; Pattern recognition (psychology); Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007885565,0.0004993281,0.0005936007,0.0007875921,0.0005252315,0.0005493566,0.0002701195,0.0005980617,0.00005970532],"category_scores_gemma":[0.0001916085,0.000622648,0.0002084588,0.001252668,0.0002046953,0.004464837,0.00007952583,0.0004366928,0.00130842],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004729023,"about_ca_system_score_gemma":0.0003239414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001138683,"about_ca_topic_score_gemma":0.00007750333,"domain_scores_codex":[0.9967602,0.0002134664,0.001592598,0.0002426159,0.0003995819,0.0007914706],"domain_scores_gemma":[0.9983664,0.000106742,0.0004270966,0.0004324587,0.0005331587,0.0001341759],"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":[0.0001931556,0.00008062971,0.003162075,0.06801233,0.000909672,0.00004347798,0.01430651,0.1096071,0.004192403,0.0339576,0.01130723,0.7542278],"study_design_scores_gemma":[0.002270352,0.0001232228,0.00287596,0.02077513,0.0004000295,0.0003084099,0.01017986,0.8059286,0.01026912,0.001542955,0.1436616,0.001664746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4766008,0.005340857,0.3851496,0.0002469053,0.03303225,0.001971763,0.0007674672,0.001604567,0.09528574],"genre_scores_gemma":[0.9925453,0.00005685807,0.005389831,0.00009848963,0.0006962436,0.0001110863,0.00031311,0.00005398509,0.0007351065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7525631,"threshold_uncertainty_score":0.9996225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01677692603956583,"score_gpt":0.2267702810568421,"score_spread":0.2099933550172763,"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."}}