{"id":"W3095961483","doi":"10.5539/ijel.v11n1p10","title":"Move Structures and Cognitive Genres in the Methods Sections of Experimental Research Articles and Corpus-Based Studies in Applied Linguistics","year":2020,"lang":"en","type":"article","venue":"International Journal of English Linguistics","topic":"Discourse Analysis in Language Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cognitive linguistics; Section (typography); Variation (astronomy); Cognition; Computer science; Applied linguistics; Corpus linguistics; Genre analysis; Contrast (vision); Research method; Linguistics; Natural language processing; Psychology; Artificial intelligence; Physics; Philosophy","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":[0.0008692437,0.00009639707,0.0002450912,0.0002622621,0.00008177607,0.00009731688,0.0001818406,0.00002340202,0.00002242418],"category_scores_gemma":[0.06995825,0.00006934395,0.00004057171,0.00008312394,0.0007881174,0.00001775874,0.00009205938,0.0003148766,1.325834e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000284067,"about_ca_system_score_gemma":0.00004229729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000506382,"about_ca_topic_score_gemma":0.000182476,"domain_scores_codex":[0.9987174,0.0001906084,0.0004464985,0.0001123695,0.0004240783,0.0001090768],"domain_scores_gemma":[0.991644,0.001783191,0.0002109085,0.00004733654,0.006281419,0.00003311942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004838051,0.0003095632,0.002988822,0.00007356678,0.0009435197,0.0001429658,0.5558096,0.0006313489,0.0001379222,0.4343602,0.0009969008,0.003121772],"study_design_scores_gemma":[0.001711808,0.0004350017,0.001095687,0.0002299506,0.0001913004,0.000001662494,0.9495092,0.0007958438,0.005965974,0.01446426,0.02540413,0.0001951967],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9048181,0.02293544,0.000141587,0.0002113302,0.00540556,0.0003203454,0.0001293758,0.00001471152,0.0660236],"genre_scores_gemma":[0.9935147,0.0001610103,0.001509268,0.00018291,0.004611567,0.000004307564,0.000002240871,0.000008082231,0.000005875927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4198959,"threshold_uncertainty_score":0.9378759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1468416757704892,"score_gpt":0.453823915681391,"score_spread":0.3069822399109018,"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."}}