{"id":"W2129316059","doi":"10.1109/crv.2008.43","title":"Thermal Faceprint: A New Thermal Face Signature Extraction for Infrared Face Recognition","year":2008,"lang":"en","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Face (sociological concept); Infrared; Artificial intelligence; Facial recognition system; Computer science; Thermal infrared; Feature extraction; Computer vision; Pattern recognition (psychology); Signature (topology); Face detection; Optics; Mathematics; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.000136022,0.0002077576,0.0001655568,0.000102573,0.0002900473,0.0001050061,0.0004191613,0.0002237074,0.0003789557],"category_scores_gemma":[0.00005332816,0.0001758712,0.0001356189,0.000229057,0.00002814252,0.00136588,0.00009796878,0.0002415776,0.0005090943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003403545,"about_ca_system_score_gemma":0.0001044587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003692338,"about_ca_topic_score_gemma":0.000004346972,"domain_scores_codex":[0.9985906,0.00005909389,0.000249924,0.0004838713,0.0002748918,0.0003416091],"domain_scores_gemma":[0.9991143,0.0001251205,0.0001233035,0.0003538966,0.0001263862,0.0001570305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001545891,0.0002212486,0.00009667747,0.00002846031,0.00004583592,0.0000175178,0.004297044,0.002255491,0.3468594,0.0003238849,0.05577622,0.5899237],"study_design_scores_gemma":[0.00426079,0.000528522,0.009892125,0.0001459973,0.00003345129,0.0001205812,0.0009348966,0.09140936,0.8287029,0.006872736,0.05564432,0.001454296],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2148688,0.00008401563,0.7742499,0.001374329,0.0004320525,0.0006092215,0.00001118405,0.0004380093,0.007932587],"genre_scores_gemma":[0.8827385,0.00007064325,0.100855,0.001455024,0.0003012677,0.0001262674,0.00008526529,0.00002991105,0.01433806],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6733948,"threshold_uncertainty_score":0.7171821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04028860312127667,"score_gpt":0.2629824102760043,"score_spread":0.2226938071547276,"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."}}