{"id":"W4401829805","doi":"10.18280/ria.380421","title":"Enhancing Question Generation in Bahasa Using Pretrained Language Models","year":2024,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Binus University","keywords":"Computer science; Natural language processing; Linguistics; Language model; Artificial intelligence; Psychology; Philosophy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002882458,0.0009711268,0.0007536623,0.0009153813,0.0004023268,0.001600582,0.001386451,0.001172893,0.003352222],"category_scores_gemma":[0.009596926,0.0003431963,0.001061571,0.0006083434,0.0004183432,0.003362556,0.001032778,0.001833858,0.002798206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001390537,"about_ca_system_score_gemma":0.001340263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009432635,"about_ca_topic_score_gemma":0.008460319,"domain_scores_codex":[0.9987558,0.0005680463,0.00009193652,0.0003964402,0.0001198712,0.00006784277],"domain_scores_gemma":[0.9946955,0.003844499,0.000165863,0.0005181569,0.0006063308,0.000169738],"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":[0.001558771,0.001585332,0.02267668,0.001985242,0.0002955434,0.0006936692,0.002276421,0.1473655,0.0342993,0.005029653,0.03832201,0.7439119],"study_design_scores_gemma":[0.0001417566,0.000458815,0.004738028,0.00007196175,0.0001044931,0.0002806783,0.0004919909,0.9528422,0.02196586,0.005033711,0.01381449,0.00005603302],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5420655,0.004202586,0.3486248,0.002435275,0.000735581,0.001409163,0.01161454,0.07191168,0.01700096],"genre_scores_gemma":[0.822943,0.0005461356,0.1500836,0.0006735462,0.00008246452,0.0004592673,0.01984532,0.0005473552,0.00481931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009432635,"threshold_uncertainty_score":0.0187555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07074700845449783,"score_gpt":0.3116321930750804,"score_spread":0.2408851846205826,"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."}}