{"id":"W4415748352","doi":"10.1109/taffc.2025.3627534","title":"Progressive Multi-Source Domain Adaptation for Personalized Facial Expression Recognition","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Affective Computing","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Bell (Canada); HEC Montréal","funders":"","keywords":"Exploit; Domain (mathematical analysis); Forgetting; Focus (optics); Similarity (geometry); Facial expression; Adaptation (eye); Face (sociological concept)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008696404,0.0008435859,0.0006825523,0.0006299543,0.000275197,0.0004457106,0.001191448,0.0006431368,0.002687006],"category_scores_gemma":[0.002587433,0.0003204202,0.0009220435,0.0005699223,0.0004837192,0.001055471,0.001262192,0.001510095,0.001629153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003734653,"about_ca_system_score_gemma":0.0005770111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003034017,"about_ca_topic_score_gemma":0.005266102,"domain_scores_codex":[0.9995188,0.0001175757,0.00002409423,0.0001769407,0.0001116919,0.00005098196],"domain_scores_gemma":[0.999419,0.0001958774,0.00003479103,0.0001603704,0.0001537519,0.00003622894],"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":[0.0003688685,0.0004131009,0.002107947,0.0001440302,0.0001441435,0.0002469723,0.0003387532,0.1437826,0.08487722,0.004009415,0.008702752,0.754864],"study_design_scores_gemma":[0.00001816169,0.00006549813,0.0009451003,0.00001313365,0.00002454185,0.0001588963,0.00005561834,0.9685372,0.02291087,0.003205318,0.004032636,0.0000330275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01753689,0.0003261071,0.9775948,0.0001036079,0.00008913979,0.0000774352,0.0001067282,0.002893617,0.001271647],"genre_scores_gemma":[0.4450897,0.0005224448,0.5448633,0.0005497369,0.0001013052,0.0003459781,0.001128077,0.0005694822,0.006829875],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003034017,"threshold_uncertainty_score":0.008988917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05386957407189527,"score_gpt":0.3495630202703141,"score_spread":0.2956934461984188,"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."}}