{"id":"W4409972601","doi":"10.1002/ail2.122","title":"A Few‐Shot Learning Approach for a Multilingual Agro‐Information Question Answering System","year":2025,"lang":"en","type":"article","venue":"Applied AI Letters","topic":"Topic Modeling","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Australian Bird Study Association; Foreign, Commonwealth and Development Office; International Development Research Centre","keywords":"Question answering; Computer science; One shot; Information retrieval; Shot (pellet); Natural language processing; Artificial intelligence; Engineering","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":[0.003232134,0.0007332273,0.0007959339,0.001167365,0.0009737901,0.001031714,0.00222291,0.001992878,0.004306268],"category_scores_gemma":[0.008832986,0.0003736228,0.000777835,0.0006040395,0.000728447,0.00296701,0.001992842,0.002166146,0.00167263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001485068,"about_ca_system_score_gemma":0.001199146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007565625,"about_ca_topic_score_gemma":0.01056891,"domain_scores_codex":[0.998089,0.0006539696,0.000116673,0.0007713953,0.0002712802,0.00009764886],"domain_scores_gemma":[0.9959413,0.002513589,0.000112308,0.0003829834,0.0008193353,0.0002305294],"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":[0.001277722,0.001523534,0.007757246,0.001009943,0.0001703139,0.001056039,0.003309217,0.06500414,0.1095834,0.006859162,0.0162078,0.7862416],"study_design_scores_gemma":[0.00004717302,0.0003037086,0.001770541,0.00002389976,0.00003826306,0.0002081645,0.0005297704,0.9562114,0.02734663,0.005892336,0.007586458,0.00004152853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1920054,0.0005759082,0.7728394,0.001418118,0.0001862119,0.0007162036,0.001669141,0.02728615,0.003303517],"genre_scores_gemma":[0.555169,0.00009125209,0.4357607,0.0006671093,0.00006922511,0.0003259317,0.003678408,0.0002441683,0.003994158],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007565625,"threshold_uncertainty_score":0.01709336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01099179054557923,"score_gpt":0.2422306152666991,"score_spread":0.2312388247211199,"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."}}