{"id":"W2026736888","doi":"10.5539/ass.v6n10p14","title":"Comparing Receptive and Productive Academic Vocabulary Knowledge of Chinese EFL Learners","year":2010,"lang":"en","type":"article","venue":"Asian Social Science","topic":"Second Language Acquisition and Learning","field":"Psychology","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vocabulary; Psychology; Vocabulary learning; English vocabulary; Mathematics education; Computer science; Linguistics","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":[0.0006853646,0.00008392343,0.0001443799,0.0001120084,0.000290181,0.00001759516,0.0002377437,0.00009386158,0.001616521],"category_scores_gemma":[0.0002089683,0.00007555027,0.00002785577,0.0006024181,0.001189388,0.0001834395,0.00007791522,0.0005788869,0.00006554979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001780889,"about_ca_system_score_gemma":0.00005697203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000327737,"about_ca_topic_score_gemma":0.00001029786,"domain_scores_codex":[0.9991102,0.00007921774,0.0001326406,0.0003197649,0.0001196885,0.0002385285],"domain_scores_gemma":[0.9995897,0.00003930195,0.0001019594,0.0001191348,0.00007033729,0.00007953845],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00004810402,0.00007162194,0.05096767,0.00001087285,0.00002127113,0.000005086238,0.5279591,1.404309e-7,0.07682823,0.01113032,0.0005366855,0.3324209],"study_design_scores_gemma":[0.0002910013,0.00003796121,0.9560562,0.000006538174,0.000005750273,0.00001738588,0.04117987,0.000009132855,0.0004689747,0.0003101266,0.001490813,0.0001262657],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7146057,0.0002517916,0.00001172729,0.0001932666,0.0004173729,0.00007771852,7.786592e-7,0.00002528003,0.2844164],"genre_scores_gemma":[0.9987048,0.000001158722,0.0001041141,0.0001952302,0.0003757763,0.000005995358,0.000001373288,0.000007167154,0.0006043975],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9050885,"threshold_uncertainty_score":0.9992961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02000591351605039,"score_gpt":0.3588792838099635,"score_spread":0.3388733702939131,"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."}}