{"id":"W4382515262","doi":"10.1002/aisy.202300050","title":"EmoSense: Revealing True Emotions Through Microgestures","year":2023,"lang":"en","type":"article","venue":"Advanced Intelligent Systems","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Hong Kong Government; Hong Kong Polytechnic University","keywords":"Stress (linguistics); Emotion detection; Capacitive sensing; Computer science; Random forest; Wearable computer; Artificial intelligence; Emotion recognition; Embedded system","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002696461,0.0002079987,0.000267029,0.0001669454,0.0002042318,0.00004243642,0.0001567528,0.000161456,0.0004526063],"category_scores_gemma":[0.0000761726,0.0001981626,0.0001405303,0.0005769972,0.00005278094,0.0001288223,0.00003295179,0.0002162874,0.007872995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005851545,"about_ca_system_score_gemma":0.00001436313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001233377,"about_ca_topic_score_gemma":0.00002163709,"domain_scores_codex":[0.9981973,0.0002009715,0.0005177304,0.0004473321,0.0001910154,0.0004456304],"domain_scores_gemma":[0.9990266,0.0001579794,0.0001678079,0.0004330036,0.0001232673,0.00009137393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003086759,0.001091672,0.002454937,0.0009062802,0.001261991,0.0005590169,0.0385853,0.01315322,0.09047141,0.2095407,0.4729807,0.1686861],"study_design_scores_gemma":[0.001345525,0.0003362865,0.004001958,0.0008837278,0.0001009397,0.0004753928,0.0348223,0.000417803,0.02082445,0.005454608,0.9302788,0.001058227],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6716692,0.006085632,0.09514286,0.001696924,0.03805584,0.003084915,0.0002098578,0.003544583,0.1805102],"genre_scores_gemma":[0.9667221,0.0004365202,0.0004792614,0.000339838,0.0004585291,0.0001312561,0.0002135205,0.00006143051,0.03115754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4572981,"threshold_uncertainty_score":0.9928995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06817276192545263,"score_gpt":0.3691302568140731,"score_spread":0.3009574948886205,"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."}}