{"id":"W4388478183","doi":"10.18280/ria.370517","title":"Class Attendance System Based on Face Recognition","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Face recognition and analysis","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Class (philosophy); Facial recognition system; Face (sociological concept); Attendance; Artificial intelligence; Computer science; Speech recognition; Psychology; Pattern recognition (psychology); Political science; Sociology; Social 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005279207,0.0001821095,0.0002167495,0.0003682475,0.0002384292,0.000172687,0.0006233654,0.00008357232,0.0001066285],"category_scores_gemma":[0.0001030388,0.0001798928,0.0001820849,0.00216861,0.00004586803,0.0002310789,0.00008162179,0.0001805419,0.01951934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008762862,"about_ca_system_score_gemma":0.0000391838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001159247,"about_ca_topic_score_gemma":0.000005801912,"domain_scores_codex":[0.9981758,0.0001147519,0.0003861615,0.0006089158,0.0003103808,0.0004040174],"domain_scores_gemma":[0.9986486,0.0002580681,0.0001218615,0.0006979763,0.0001407324,0.0001327197],"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":[0.00002390108,0.0002569552,0.0001537039,0.0003252783,0.00004208616,0.0001636423,0.0008654312,0.4201582,0.004512934,0.01571907,0.006930762,0.5508481],"study_design_scores_gemma":[0.00003871556,0.00006599535,0.00002927085,0.000232887,0.000007973829,0.000007078011,0.0006409163,0.9580439,0.03716379,0.0003954556,0.003149037,0.0002249456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007939216,0.00002796261,0.974992,0.004266862,0.0005832379,0.000227549,0.00001894727,0.001129063,0.01081512],"genre_scores_gemma":[0.9945877,0.0000296845,0.002405857,0.0005112102,0.00007317114,0.00005555617,0.00003867305,0.00001722962,0.002280929],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9866485,"threshold_uncertainty_score":0.9812441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05907671994489123,"score_gpt":0.270067142163886,"score_spread":0.2109904222189948,"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."}}