{"id":"W2755237317","doi":"10.1111/lang.12253","title":"The Academic Spoken Word List","year":2017,"lang":"en","type":"article","venue":"Language Learning","topic":"Second Language Acquisition and Learning","field":"Psychology","cited_by":213,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Vocabulary; Linguistics; British National Corpus; Computer science; Spoken language; English for academic purposes; American English; Word lists by frequency; Discipline; Lexical density; Psychology; Word list; Natural language processing; Lexical item; World Wide Web; Index (typography); Sociology; Sentence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000753856,0.0001467021,0.0001442025,0.00004780981,0.002077237,0.0003261106,0.0007567807,0.0001556692,0.0302594],"category_scores_gemma":[0.000863278,0.0001084252,0.00009244413,0.00005425105,0.0001600576,0.0001409602,0.0001411361,0.001338221,0.002129452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002197476,"about_ca_system_score_gemma":0.00001232003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004454351,"about_ca_topic_score_gemma":0.00003982476,"domain_scores_codex":[0.9986258,0.0002512666,0.0002020471,0.0002897782,0.0001690956,0.0004620718],"domain_scores_gemma":[0.9984623,0.0003094015,0.0002804753,0.0008275051,0.00002570568,0.00009465146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000148192,0.00002609564,0.02511732,0.0000117389,0.0001419496,0.0009465147,0.07056071,0.00003429624,0.003153827,0.01064164,0.01001454,0.8792032],"study_design_scores_gemma":[0.001157233,0.00006722472,0.2078688,0.00006213813,0.00003612193,0.0001538832,0.07254402,0.0001684976,0.0002549097,0.0001031335,0.7171485,0.0004355904],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7651992,0.01177164,0.00009046918,0.001366465,0.0009657796,0.0001182152,0.000001280316,0.0002404197,0.2202465],"genre_scores_gemma":[0.8847122,0.0000203677,0.0000471137,0.00205075,0.0009135269,0.00002116768,0.00001048877,0.00003551861,0.1121888],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8787676,"threshold_uncertainty_score":0.9992219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01957480886760424,"score_gpt":0.3672021094661021,"score_spread":0.3476273005984979,"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."}}