{"id":"W4387421718","doi":"10.1145/3577190.3614141","title":"Toward Fair Facial Expression Recognition with Improved Distribution Alignment","year":2023,"lang":"en","type":"article","venue":"INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION","topic":"Face recognition and analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Estimator; Computer science; Kernel (algebra); Classifier (UML); Artificial intelligence; Pattern recognition (psychology); Facial expression; Attractiveness; Expression (computer science); Facial expression recognition; Machine learning; Mathematics; Facial recognition system; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001646683,0.0002054591,0.0001535708,0.000279694,0.0001322792,0.0003594225,0.0004187573,0.00008847333,0.0004226591],"category_scores_gemma":[0.00007106186,0.0001740554,0.0001088639,0.0003458424,0.00003246767,0.001064671,0.0001101373,0.0002353447,0.001166659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002286691,"about_ca_system_score_gemma":0.00004882391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009815146,"about_ca_topic_score_gemma":0.00002550883,"domain_scores_codex":[0.9983341,0.00008022556,0.000297115,0.0005262044,0.0005249829,0.0002374363],"domain_scores_gemma":[0.9989719,0.0000705049,0.0002000688,0.0002114998,0.0004417262,0.0001042918],"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":[0.0008997465,0.0007509569,0.0004392795,0.00003327518,0.0003092081,0.00008273721,0.00155804,0.002302161,0.2234471,0.01043033,0.003550805,0.7561963],"study_design_scores_gemma":[0.0010952,0.0002938554,0.001355399,0.0002354164,0.00001539967,0.00002068712,0.0007535794,0.9102862,0.08068511,0.002155881,0.002708155,0.0003951083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.276602,0.000002373648,0.7006798,0.008695207,0.002791582,0.0005069981,0.0002981803,0.001093948,0.009329913],"genre_scores_gemma":[0.995918,0.00004420966,0.001923279,0.0001852747,0.0001346497,0.0001073933,0.001225723,0.00001065523,0.0004508445],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9079841,"threshold_uncertainty_score":0.999611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07736451981218141,"score_gpt":0.3196333882038205,"score_spread":0.2422688683916391,"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."}}