{"id":"W4210702106","doi":"10.1109/fg52635.2021.9666986","title":"Face Trees for Expression Recognition","year":2021,"lang":"en","type":"article","venue":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Tree traversal; Computer science; Landmark; Artificial intelligence; Expression (computer science); Embedding; Pattern recognition (psychology); Tree (set theory); Face (sociological concept); Architecture; Scale (ratio); Component (thermodynamics); Host (biology); Facial recognition system; Facial expression; Algorithm; Mathematics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003255419,0.0003846519,0.0003945036,0.0002645123,0.0002222256,0.0002466652,0.0001904896,0.0003777937,0.02494929],"category_scores_gemma":[0.0003008375,0.0003755305,0.0002055922,0.0002230253,0.00008508938,0.0003046308,0.00004595114,0.0003959425,0.001651007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007002146,"about_ca_system_score_gemma":0.0001151077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001650578,"about_ca_topic_score_gemma":0.0000837411,"domain_scores_codex":[0.9974205,0.0002881548,0.0006103467,0.000849727,0.0004541111,0.0003771112],"domain_scores_gemma":[0.997968,0.0003786296,0.0003267607,0.0002990532,0.0008307982,0.0001968139],"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":[0.0002507756,0.0009266246,0.00010441,0.0001293283,0.000364367,0.00007451098,0.00231759,0.0000120106,0.01711627,0.001514983,0.02721014,0.949979],"study_design_scores_gemma":[0.04690924,0.005411543,0.03727105,0.01944502,0.001966972,0.002475093,0.1088563,0.06936494,0.3637402,0.1924299,0.1421573,0.00997235],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6832111,0.000860055,0.06828742,0.02517573,0.01725062,0.003088266,0.003583302,0.0005800084,0.1979635],"genre_scores_gemma":[0.9692363,0.001137395,0.004211392,0.001977546,0.00102987,0.0007656073,0.004834675,0.00007423772,0.01673299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9400066,"threshold_uncertainty_score":0.9998696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09484208444964427,"score_gpt":0.3551049256135598,"score_spread":0.2602628411639155,"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."}}