{"id":"W2336444531","doi":"10.1145/2896338.2896368","title":"Emotional Virtual Agent to Improve Ageing in Place with Technology","year":2016,"lang":"en","type":"article","venue":"","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Ageing; Human–computer interaction","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":[0.001625597,0.0003923803,0.0002029039,0.00048296,0.0006744315,0.001381267,0.0004845855,0.0004402643,0.004439996],"category_scores_gemma":[0.003837179,0.0001023345,0.000352312,0.0001945191,0.0004665351,0.001185169,0.002039556,0.0004023991,0.000531405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003184701,"about_ca_system_score_gemma":0.0004441343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000311436,"about_ca_topic_score_gemma":0.0005956168,"domain_scores_codex":[0.9990016,0.000713146,0.00004783484,0.00005837368,0.0001122753,0.00006675696],"domain_scores_gemma":[0.9991386,0.0003845811,0.00008828202,0.00009222551,0.0001333719,0.0001629739],"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":[0.001279471,0.005419182,0.01683682,0.002984171,0.0001667867,0.0008968815,0.05333575,0.004902701,0.04827993,0.05554238,0.01576786,0.7945881],"study_design_scores_gemma":[0.0009045842,0.01561967,0.08524369,0.002218827,0.001295065,0.002553125,0.05619477,0.0361573,0.04831545,0.04981805,0.7013012,0.0003782534],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.720629,0.002138129,0.1652771,0.001951976,0.0006587244,0.001183836,0.0001530859,0.001014717,0.1069935],"genre_scores_gemma":[0.9120942,0.0006532174,0.07637531,0.0004057221,0.00004147826,0.0005513882,0.00006925168,0.00006245298,0.009747006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004439996,"threshold_uncertainty_score":0.0148533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00895577353971539,"score_gpt":0.2587388744885802,"score_spread":0.2497831009488649,"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."}}