{"id":"W1523511218","doi":"10.3968/6267","title":"The Use of Concordance Programs in English Lexical Teaching in High School","year":2015,"lang":"en","type":"article","venue":"Higher education of social science","topic":"Second Language Acquisition and Learning","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Concordance; Computer science; Corpus linguistics; Linguistics; Natural language processing; Mathematics education; Artificial intelligence; Psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.0009535037,0.00004723193,0.0000912983,0.00009037644,0.00008387557,0.00004063833,0.0002242009,0.00004405227,0.0006504523],"category_scores_gemma":[0.0003728677,0.00003886716,0.00001796416,0.000519652,0.0004182424,0.0002276648,0.0000245774,0.0001985657,0.000009187463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009865691,"about_ca_system_score_gemma":0.0002946433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001103478,"about_ca_topic_score_gemma":0.00002048602,"domain_scores_codex":[0.9990565,0.0001799556,0.0002234925,0.0001512545,0.0002159602,0.0001728441],"domain_scores_gemma":[0.9994534,0.00009902302,0.0001346723,0.0001231131,0.000126989,0.00006276045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00006378124,0.0005970241,0.1238909,0.000006835163,0.000003977405,0.000001313338,0.09087249,0.00001034437,0.0004953862,0.7464154,0.004743751,0.03289879],"study_design_scores_gemma":[0.0003241633,0.00004047212,0.9075513,0.00002102217,0.000001431308,4.626069e-7,0.01863067,0.000003152435,0.00002674957,0.0004083908,0.07293285,0.00005936372],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9707614,0.0002433959,0.000004408842,0.0003495518,0.001232109,0.0001233407,5.21308e-7,0.0000134128,0.02727189],"genre_scores_gemma":[0.9960331,5.266805e-7,0.0002564243,0.0006166876,0.0002027382,0.0000255148,0.000002240547,0.000003709398,0.002859039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7836604,"threshold_uncertainty_score":0.7121996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07323884235233785,"score_gpt":0.3805806210533551,"score_spread":0.3073417787010173,"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."}}