{"id":"W4414882152","doi":"10.48084/etasr.12761","title":"A Response-by-Retrieval Chatbot for Enhancing Horticulture Extension Services in Tanzania","year":2025,"lang":"en","type":"article","venue":"Engineering Technology & Applied Science Research","topic":"AI in Service Interactions","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Chatbot; Credibility; Key (lock); Government (linguistics); Revenue; Encoder; Software deployment; Language model","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001522237,0.001427611,0.0007083248,0.0008411229,0.0009424104,0.0005403566,0.00129139,0.001344193,0.007431157],"category_scores_gemma":[0.00467204,0.0002951349,0.0004760689,0.0004829439,0.0003932738,0.001956395,0.00167343,0.001130302,0.003713752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009178699,"about_ca_system_score_gemma":0.000941577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008313215,"about_ca_topic_score_gemma":0.02414184,"domain_scores_codex":[0.9988956,0.0005757947,0.00006281392,0.0002598802,0.00009635883,0.0001094276],"domain_scores_gemma":[0.9972263,0.001904403,0.0001003155,0.0002041914,0.0002302021,0.0003345618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.007694791,0.005794697,0.02981242,0.01046518,0.0002581064,0.009059993,0.01921935,0.01617459,0.121222,0.002695503,0.2515725,0.5260309],"study_design_scores_gemma":[0.001716693,0.008736569,0.1339983,0.001584114,0.0004323695,0.005220978,0.02415938,0.4202177,0.08176509,0.006356893,0.3151251,0.0006867667],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.918919,0.00237623,0.02235886,0.001036794,0.0005374308,0.001817083,0.0209374,0.02308329,0.008933835],"genre_scores_gemma":[0.786561,0.000594374,0.1171449,0.001171467,0.0001623156,0.001960001,0.06786104,0.0006515196,0.0238934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008313215,"threshold_uncertainty_score":0.02485967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01262882439108442,"score_gpt":0.3300004618410143,"score_spread":0.3173716374499299,"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."}}