{"id":"W4229448254","doi":"10.18280/ts.390228","title":"Expression Identification and Emotional Classification of Students in Job Interviews Based on Image Processing","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Educational Technology and Pedagogy","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Expression (computer science); Set (abstract data type); Job interview; Computer science; Emotional expression; Histogram; Artificial intelligence; Representation (politics); Image processing; Graph; Artificial neural network; Psychology; Image (mathematics); Pattern recognition (psychology); Social psychology; Theoretical computer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004364789,0.0002976966,0.0002144823,0.0004928847,0.0002080842,0.0003962831,0.0002347799,0.0002690804,0.0008490725],"category_scores_gemma":[0.001215196,0.00007879054,0.0002761758,0.0002955562,0.0002573789,0.0003719699,0.000394845,0.0002734035,0.0002846927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000181942,"about_ca_system_score_gemma":0.0001577419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000520621,"about_ca_topic_score_gemma":0.0007857517,"domain_scores_codex":[0.9996952,0.0001007468,0.00001230288,0.00006538732,0.00006984495,0.00005662283],"domain_scores_gemma":[0.9997212,0.00009937402,0.00004231338,0.0000226226,0.00008194343,0.00003247049],"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":[0.00125262,0.0002540964,0.04868765,0.0002325664,0.0000520154,0.0004929531,0.00323766,0.007978312,0.316393,0.002078812,0.002123726,0.6172166],"study_design_scores_gemma":[0.00004407927,0.0009674458,0.2739761,0.00006599675,0.000143969,0.0009402277,0.008604493,0.4962143,0.208696,0.00401394,0.006200664,0.00013279],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7808818,0.0001345395,0.2148541,0.0001876309,0.0000457629,0.0001086198,0.00009554622,0.0002955192,0.003396593],"genre_scores_gemma":[0.9594711,0.0001121986,0.03847136,0.0000426608,0.00001787206,0.00005671075,0.00009625687,0.00002047915,0.00171129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008490725,"threshold_uncertainty_score":0.0028404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04899376216477591,"score_gpt":0.3387056407283213,"score_spread":0.2897118785635454,"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."}}