Bibliographic record
Abstract
World Journal of English Language wishes to acknowledge the following individuals for their assistance with peer review of manuscripts for this issue. Their help and contributions in maintaining the quality of the journal are greatly appreciated.World Journal of English Language is recruiting reviewers for the journal. If you are interested in becoming a reviewer, we welcome you to join us. Please contact us for the application form at: wjel@sciedupress.comReviewers for Volume 11, Number 2Andrés Canga, University of La Rioja, SpainChunlin Yao, Tianjin Chengjian University, ChinaDaniel Ginting, Universitas Ma Chung, IndonesiaDon Anton Balida, Oman Tourism College, OmanElena Alcalde Peñalver, University of Alcalá, SpainEmine Bala, Tishk International University, IraqGhadah Al Murshidi, The United Arab Emirates University, UAEHameed Yahya Ahmed Al-Zubeiry, Al-Baha University, Saudi ArabiaHossein Salarian, University of Tehran, IranHouaria Chaal, Hassiba Ben Bouali University of Chlef, AlgeriaJasna Potocnik Topler, University of Maribor, SloveniaKanthimathi Krishnasamy, Shrimathi Devkunvar Nanalal Bhatt Vaishnav College for Women, IndiaKenan Yerli, Sakarya University, TurkeyLeila Lomashvili, Shawnee State University, USALi Ping Chang, Department of Applied Foreign Languages, National Taipei College of Business, TaiwanMaria del Mar Sanchez Ramos, University of Alcalá, SpainMaria Isabel Maldonado Garcia, Al-Andalus Institute of Languages University of Lahore, PakistanMaría Luisa Carrió, Universidad Politécnica de Valencia, SpainMuhammed Ibrahim Hamood, University of Mosul, IraqMustafa Ar, Ar-Raniry State Islamic University, IndonesiaNitin Malhotra, St. Theresa International College, Bangkok, ThailandÖzkanal, Ümit, Eskisehir Osmangazi University Foreign Languages Department, TurkeyPatnarin Supakorn, Walailak University, ThailandPham Vu Phi Ho, Van Lang University, VietnamScott-Monkhouse Anila Ruth, Language Centre – University of Parma (Italy), ItalyŞenel, Müfit, 19 Mayıs University, TurkeyShalini Yadav, Compucom Institute of Technology and Management, IndiaTeguh Budiharso, State Institute of Islamic Studies (IAIN) of Surakarta, Indonesia, IndonesiaWafi Fhaid Alshammari, University of Ha’il, Saudi ArabiaWenjie Shi, Central University of Finance and Economics, China
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.054 | 0.549 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.007 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.180 | 0.115 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".