{"id":"W2054949702","doi":"10.5539/ijel.v1n2p252","title":"Error Recognition Tests as a Predictor of EFL Learners' Writing Ability","year":2011,"lang":"en","type":"article","venue":"International Journal of English Linguistics","topic":"Educational Technology and Assessment","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Test (biology); Pearson product-moment correlation coefficient; Psychology; Correlation; Construct (python library); Measure (data warehouse); Mathematics education; Statistics; Cognitive psychology; Computer science; Mathematics; Data mining","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":[0.0006567118,0.00008223274,0.000136582,0.0001917308,0.0000297889,0.00003240095,0.0009579726,0.00008386756,0.00007050283],"category_scores_gemma":[0.04297797,0.00007914531,0.00007737064,0.000112299,0.00008321162,0.0001461598,0.00009443452,0.0003148254,0.000006058498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007106869,"about_ca_system_score_gemma":0.0002697265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001058214,"about_ca_topic_score_gemma":0.000001585723,"domain_scores_codex":[0.9986867,0.00004828367,0.0005636464,0.0001286557,0.0004681583,0.0001046082],"domain_scores_gemma":[0.9849582,0.0002956987,0.0005754138,0.0001564089,0.01395238,0.0000619414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003051755,0.004177937,0.2095422,0.0001107064,0.001021938,0.0002586629,0.01664547,0.0001554613,0.0006353192,0.7194995,0.007344325,0.04030333],"study_design_scores_gemma":[0.004152468,0.002552972,0.1799763,0.001290085,0.0002123687,0.0001475031,0.006926806,0.002532608,0.03939618,0.6821747,0.07963047,0.001007475],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.792127,0.0002074066,0.02798492,0.0003324412,0.03839301,0.000192673,0.00005115404,0.0001524783,0.1405589],"genre_scores_gemma":[0.9374725,0.00001442074,0.06026511,0.00007413047,0.002141991,0.000001790903,0.00000404442,0.00000498093,0.00002105851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1453455,"threshold_uncertainty_score":0.9650834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04292484347527174,"score_gpt":0.3282509662089685,"score_spread":0.2853261227336967,"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."}}