{"id":"W2971003348","doi":"10.5539/ijel.v9n5p138","title":"“Instructing” the Cruxes of Language Errors: Diagnosing the EFL Students’ Significant Translation Errors","year":2019,"lang":"en","type":"article","venue":"International Journal of English Linguistics","topic":"English Language Learning and Teaching","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nonprobability sampling; Sample (material); Psychology; Class (philosophy); Mathematics education; Population; Computer science; Sociology; Artificial intelligence; Chemistry; Demography","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001498702,0.0001252529,0.0001850978,0.0001360718,0.00008673339,0.0002557465,0.002171886,0.00005122437,0.00001849189],"category_scores_gemma":[0.02553336,0.00007666793,0.0001558072,0.0001595862,0.00006656617,0.0001573949,0.000140312,0.0006193438,0.000002806173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004939048,"about_ca_system_score_gemma":0.00007203421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004835262,"about_ca_topic_score_gemma":0.000007885304,"domain_scores_codex":[0.9978804,0.0002065018,0.0005731915,0.0001435659,0.001039917,0.000156434],"domain_scores_gemma":[0.9936934,0.001265806,0.0007298593,0.0002987562,0.003967894,0.00004425204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002221212,0.0008535687,0.2918451,0.0001304948,0.001736171,0.0004031392,0.452083,0.0690931,0.001805308,0.07855242,0.002438039,0.1008375],"study_design_scores_gemma":[0.0169493,0.002733757,0.1365386,0.005379468,0.00101315,0.0002443264,0.219895,0.0781886,0.03699682,0.01116597,0.4875625,0.003332431],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9581317,0.0006273867,0.01299456,0.0002313316,0.01942833,0.0001502391,0.000007114436,0.00004990789,0.008379425],"genre_scores_gemma":[0.9898583,0.00002306191,0.006174037,0.0001350381,0.003755468,9.527464e-7,0.000002073006,0.00001288986,0.00003821729],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4851245,"threshold_uncertainty_score":0.982675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01378244829741718,"score_gpt":0.2914667571132185,"score_spread":0.2776843088158013,"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."}}