{"id":"W2996908621","doi":"10.1109/icmla.2019.00309","title":"A Voice Interactive Multilingual Student Support System using IBM Watson","year":2019,"lang":"en","type":"preprint","venue":"","topic":"AI in Service Interactions","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Chatbot; Computer science; IBM; Personalization; Watson; World Wide Web; Dialog system; Human–computer interaction; Artificial intelligence","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":[0.0006500739,0.0007592012,0.0003536393,0.0005130586,0.0004241778,0.0008589526,0.0006530882,0.0004436416,0.0146703],"category_scores_gemma":[0.001695882,0.0002500375,0.0002628972,0.0003622138,0.0002142856,0.0007854758,0.001262701,0.0005217541,0.004256444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002370148,"about_ca_system_score_gemma":0.0003841919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00113982,"about_ca_topic_score_gemma":0.0009775735,"domain_scores_codex":[0.9995657,0.0001143217,0.00003305957,0.0001071034,0.0001285847,0.00005135424],"domain_scores_gemma":[0.9992963,0.0002595925,0.00005630537,0.00009932306,0.0001522912,0.0001361247],"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":[0.005003544,0.0008617422,0.006738342,0.0006935307,0.0001286383,0.002670994,0.00587023,0.00166217,0.3226316,0.00581714,0.03939273,0.6085293],"study_design_scores_gemma":[0.001585769,0.007084294,0.03247698,0.0002425785,0.0005583008,0.005553988,0.004126952,0.1644827,0.3547772,0.006942184,0.4217301,0.0004389166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3229601,0.0005883227,0.4340526,0.0003404778,0.000234207,0.001612251,0.001177215,0.1932245,0.04581034],"genre_scores_gemma":[0.7744878,0.0002482916,0.153987,0.0003684782,0.0001121169,0.0008288885,0.002345121,0.003419878,0.0642026],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0146703,"threshold_uncertainty_score":0.04907709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0410448649379407,"score_gpt":0.3660133112151571,"score_spread":0.3249684462772164,"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."}}