{"id":"W4382618909","doi":"10.5430/wjel.v13n5p501","title":"Analysis Methods of Vietnamese Sentence and Culture in Vietnamese Sentences","year":2023,"lang":"en","type":"article","venue":"World Journal of English Language","topic":"Evaluation Methods in Various Fields","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vietnamese; Sentence; Computer science; Linguistics; Natural language processing; Grammar; Artificial intelligence; Scope (computer science); 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004542321,0.0001227075,0.0004056002,0.0005194263,0.00003819638,0.00002299867,0.0003029301,0.00006400622,0.0009444586],"category_scores_gemma":[0.003045451,0.00009589532,0.0001657026,0.003269655,0.0001537247,0.0002450324,0.0001608447,0.0003560967,0.000006242028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006150515,"about_ca_system_score_gemma":0.0000170082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001125871,"about_ca_topic_score_gemma":0.001094197,"domain_scores_codex":[0.9978994,0.0006373423,0.0005812556,0.0001894052,0.0004912412,0.0002013829],"domain_scores_gemma":[0.9988328,0.0003505674,0.000411256,0.000214699,0.00009045997,0.0001001795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006473809,0.0001283806,0.6998681,0.00005014873,0.0003117239,0.000201711,0.2042682,0.01244488,0.02022047,0.00008875007,0.003408138,0.0589447],"study_design_scores_gemma":[0.003698333,0.0005945556,0.6846736,0.0005402548,0.001885307,0.00007141327,0.2344818,0.02982244,0.01695842,0.005851778,0.02011318,0.001308896],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9873944,0.001176438,0.002952915,0.0003532338,0.0004170549,0.0001286376,0.000006257452,0.00002575294,0.007545347],"genre_scores_gemma":[0.8387053,0.000327171,0.1590047,0.0001458848,0.0001040915,0.000003080084,0.000002334672,0.00001072652,0.001696709],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1560518,"threshold_uncertainty_score":0.9999688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01796452478556193,"score_gpt":0.3590170997199564,"score_spread":0.3410525749343944,"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."}}