{"id":"W2955825940","doi":"10.24908/iqurcp.13261","title":"Personalizing Chatbot Conversations with IBM Watson","year":2019,"lang":"en","type":"article","venue":"Inquiry Queen s Undergraduate Research Conference Proceedings","topic":"AI in Service Interactions","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Watson; Chatbot; Computer science; IBM; Personalization; Human–computer interaction; World Wide Web; User interface; Interactivity; Multimedia; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00129741,0.0003467179,0.0003519724,0.0006895981,0.0005557153,0.00156173,0.002151889,0.0001590419,0.0001801602],"category_scores_gemma":[0.0001519176,0.0003031142,0.00008942506,0.001802725,0.0004548556,0.003721481,0.0007832697,0.001195562,0.001691002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004480034,"about_ca_system_score_gemma":0.000776847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005960176,"about_ca_topic_score_gemma":0.00004182072,"domain_scores_codex":[0.9952276,0.0001088144,0.000401586,0.001150041,0.001913823,0.00119808],"domain_scores_gemma":[0.9952992,0.0004209286,0.0001910494,0.0006427783,0.003065095,0.0003810114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000806418,0.0001857921,0.01261499,0.0002440706,0.000145988,0.00002648145,0.02303979,0.00002115786,0.01116281,0.9428664,0.006514898,0.003096974],"study_design_scores_gemma":[0.006600967,0.00550612,0.01059708,0.003942241,0.0001070135,0.000815907,0.1064378,0.2624078,0.04851973,0.4080013,0.1418,0.005264088],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4422978,0.0001001382,0.1998137,0.2692491,0.001322172,0.003113752,0.00001016255,0.001631361,0.0824619],"genre_scores_gemma":[0.9842446,0.0001079747,0.01119228,0.0003631422,0.0001651679,0.000169287,0.000007269487,0.00004362615,0.003706659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5419468,"threshold_uncertainty_score":0.9999421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07984889944994816,"score_gpt":0.3519050561530785,"score_spread":0.2720561567031303,"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."}}