{"id":"W2387787538","doi":"10.1115/1.4033226","title":"Affective Voice Recognition of Older Adults1","year":2016,"lang":"en","type":"article","venue":"Journal of Medical Devices","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Loneliness; Psychology; Facial expression; Affect (linguistics); Intonation (linguistics); Body language; Social isolation; Cognition; Cognitive psychology; Social robot; Social relation; Robot; Computer science; Social psychology; Communication; Artificial intelligence; Psychotherapist; Linguistics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001022276,0.00007383252,0.0002084625,0.0001440765,0.00001933759,0.00000499563,0.0001551662,0.0001856745,0.007873238],"category_scores_gemma":[0.0005996396,0.0000413956,0.0001229955,0.0001038633,0.00008605245,0.0001450655,0.00001514343,0.0001928133,0.0003470722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001851527,"about_ca_system_score_gemma":0.00005354982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001624403,"about_ca_topic_score_gemma":0.00003774044,"domain_scores_codex":[0.9984585,0.0002445077,0.0004576295,0.00009511033,0.0006198562,0.0001243958],"domain_scores_gemma":[0.9984086,0.0004909656,0.0005092819,0.00006528781,0.0003465602,0.0001793536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001798762,0.0004103739,0.002451113,0.00005104576,0.0001726892,0.0000611245,0.0009149923,1.776936e-8,0.0007278911,0.0001992164,0.01169237,0.9831393],"study_design_scores_gemma":[0.02766288,0.004460617,0.8360224,0.0136057,0.0006735262,0.003095172,0.008356598,0.00001788541,0.02052026,0.01063827,0.0741998,0.0007468306],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9709067,0.0005694333,0.005236307,0.00809474,0.002302289,0.0001001224,0.00001240602,0.00001441743,0.01276362],"genre_scores_gemma":[0.9980611,0.0002452094,0.0001587122,0.0006642084,0.0006121705,0.00000246721,0.00000169644,0.000008248016,0.000246139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9823924,"threshold_uncertainty_score":0.9930337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02894646318239564,"score_gpt":0.3410842778012275,"score_spread":0.3121378146188319,"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."}}