{"id":"W2745180147","doi":"10.5539/elt.v10n9p61","title":"Online Corpus Tools in Scholarly Writing: A Case of EFL Postgraduate Student","year":2017,"lang":"en","type":"article","venue":"English Language Teaching","topic":"Lexicography and Language Studies","field":"Arts and Humanities","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universiti Putra Malaysia","keywords":"Collocation (remote sensing); Context (archaeology); Corpus linguistics; Session (web analytics); Psychology; Computer science; Natural language processing; Linguistics; Proofreading; Academic writing; Computational linguistics; World Wide Web; Mathematics education","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007871328,0.0007544585,0.0007659573,0.002694878,0.01486028,0.006602905,0.002890194,0.00456937,0.005939718],"category_scores_gemma":[0.03306089,0.0006203821,0.0004504326,0.0025801,0.01009363,0.005218789,0.008568318,0.004912911,0.001746416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003306993,"about_ca_system_score_gemma":0.003362272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004007049,"about_ca_topic_score_gemma":0.00896621,"domain_scores_codex":[0.9891425,0.006607269,0.0005074944,0.0008830451,0.001868888,0.0009908648],"domain_scores_gemma":[0.9772834,0.01395947,0.002300436,0.001409917,0.001609921,0.003436802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0000489205,0.000362478,0.006277086,0.0001874909,0.000008043125,0.04035234,0.9183879,0.0001018374,0.001453426,0.003096573,0.002726794,0.02699701],"study_design_scores_gemma":[0.00001765158,0.0002636408,0.004537783,0.0002244802,0.00001625186,0.05124783,0.8856484,0.001070398,0.00217006,0.002677894,0.05205918,0.00006656659],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9720464,0.0006441032,0.00448716,0.007241057,0.0001300332,0.00008900012,0.0000638904,0.0001462524,0.01515213],"genre_scores_gemma":[0.9795527,0.0005116171,0.005461328,0.001416931,0.00008350358,0.00005459471,0.00004166359,0.0001332632,0.01274451],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01486028,"threshold_uncertainty_score":0.04162806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04464154770637116,"score_gpt":0.3194124023439035,"score_spread":0.2747708546375324,"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."}}