{"id":"W4410087685","doi":"10.1109/wi-iat62293.2024.00043","title":"Developing A Chatbot: A Hybrid Approach Using Deep Learning and RAG","year":2024,"lang":"en","type":"article","venue":"","topic":"AI in Service Interactions","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Lakehead University","funders":"Lakehead University","keywords":"Chatbot; Computer science; Deep learning; Artificial intelligence; Human–computer interaction; Natural language processing","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00123072,0.001090027,0.0006095379,0.0007264127,0.0004767569,0.001275787,0.00237042,0.001496055,0.004425921],"category_scores_gemma":[0.002285073,0.0004908132,0.0006078827,0.0004644153,0.000566282,0.00281253,0.001851991,0.001772542,0.002050456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007007545,"about_ca_system_score_gemma":0.001105757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003343752,"about_ca_topic_score_gemma":0.00680885,"domain_scores_codex":[0.9994258,0.0001419976,0.00003309216,0.0001777909,0.000140491,0.00008085379],"domain_scores_gemma":[0.9990839,0.0003776113,0.00004281535,0.0001848666,0.0001905797,0.0001203619],"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":[0.0006358242,0.001463046,0.003479391,0.0005343266,0.0002232796,0.0007851194,0.001010486,0.08813923,0.06366666,0.01068557,0.01413069,0.8152464],"study_design_scores_gemma":[0.0000382459,0.0003067933,0.0004625076,0.00003100812,0.00005170279,0.0001468949,0.0002073228,0.9654511,0.01849822,0.006455719,0.008315737,0.00003473519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0572188,0.000470693,0.9085615,0.0005760154,0.0001822712,0.0003107576,0.0002445205,0.02467047,0.007764862],"genre_scores_gemma":[0.4264801,0.0002323885,0.5576966,0.00061621,0.00006171501,0.0003566704,0.0009128549,0.0006486941,0.01299478],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004425921,"threshold_uncertainty_score":0.01480615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03591839200117003,"score_gpt":0.3016671694065624,"score_spread":0.2657487774053924,"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."}}