{"id":"W4390244753","doi":"10.18280/ria.370612","title":"Intelligent Vehicle Driver Face and Conscious Recognition","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Facial recognition system; Computer science; Face (sociological concept); Artificial intelligence; Human–computer interaction; Computer vision; Pattern recognition (psychology); Sociology","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":[0.0003564896,0.0001562549,0.0001596127,0.0002043616,0.0002363743,0.0001731404,0.0003862871,0.00009185967,0.0001314299],"category_scores_gemma":[0.0001064954,0.0001537049,0.0000644631,0.000808564,0.00009512089,0.0004254036,0.0002744129,0.0001650077,0.006655702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002440676,"about_ca_system_score_gemma":0.00002331918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002089974,"about_ca_topic_score_gemma":0.000006767496,"domain_scores_codex":[0.9985386,0.00006633631,0.0003237813,0.0005191902,0.000185764,0.000366394],"domain_scores_gemma":[0.9990424,0.0002115767,0.00008177283,0.0004129388,0.0001062619,0.000145076],"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":[0.00001468252,0.0001101894,0.0003643872,0.00007175762,0.00001981924,0.00006966685,0.005141614,0.003352856,0.0278722,0.00335356,0.009372841,0.9502564],"study_design_scores_gemma":[0.00006647893,0.0001207483,0.0002361604,0.0001606559,0.00000843934,0.00004067078,0.001593614,0.7080621,0.2580219,0.02011284,0.01120679,0.0003696602],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4397136,0.0002867655,0.5514663,0.003195243,0.0008861135,0.0004391291,0.00001279277,0.0008435751,0.00315645],"genre_scores_gemma":[0.9939797,0.0007957832,0.00267696,0.0003680979,0.00006585209,0.00004454204,0.00002331958,0.00001557379,0.002030194],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9498867,"threshold_uncertainty_score":0.9941177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05433858196165731,"score_gpt":0.2745980259288356,"score_spread":0.2202594439671783,"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."}}