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 12, Number 8Abdulfattah Omar, Prince Sattam Bin Abdulaziz University, Saudi ArabiaAcep Unang Rahayu, Poltekpar NHI Bandung, IndonesiaAli Hussein Hazem, University of Patras, GreeceAmelia Maria Cava, Università di Napoli Suor Orsola Benincasa, ItalyAmer M Th Ahmed, Dhofar University, OmanAna Maria Costa Lopes, Higher School of Education of the Polytechnic Institute of Viseu, PortugalAndrés Canga , University of La Rioja, SpainAnna Maria Kuzio, University of Zielona Gora, PolandAyman Khafaga, Suez Canal University, EgyptBelén Labrador de la Cruz, University of León, SpainDaniel Ginting, Universitas Ma Chung, IndonesiaDon Anton Balida, International College of Engineering and Management, OmanEmine Bala, Independent Researcher, NetherlandsHameed Yahya Ahmed Al-Zubeiry, Al-Baha University, Saudi ArabiaHANY ALI MAHMOUD ABDELFATTAH, Minia University, EgyptHossein Salarian, University of Tehran, IranHouaria Chaal, Hassiba Ben Bouali University of Chlef, AlgeriaKanthimathi Krishnasamy, Shrimathi Devkunvar Nanalal Bhatt Vaishnav College for Women, IndiaKaya özçelik, Atılım University, TurkeyL. Santhosh Kumar, Kristu Jayanti College (Autonomous), IndiaLeila Lomashvili, Shawnee State University, USALi Ping Chang, Department of Applied Foreign Languages, National Taipei College of Business, TaiwanMohamad Fadhili bin Yahaya, Universiti Teknologi Mara Perlis Branch, MalaysiaMorteza Amirsheibani, Ferdowsi University of Mashhad, IranMovva Srilakshmi, Prasad V. Potluri Siddhartha Institute of Technology, IndiaMuhammed Ibrahim Hamood, University of Mosul, IraqNing Li, Guangdong Pharmaceutical University (GDPU), ChinaNitin Malhotra, Gobindgarh Public College, IndiaÖzkanal, Ümit, Eskisehir Osmangazi University Foreign Languages Department, TurkeyRashad Al Areqi, Al Baha University, KSASantri Djahimo, Nusa Cendana University, IndonesiaŞenel, Müfit, 19 Mayıs University, TurkeyServais Dieu-Donné Yédia DADJO, University of Abomey-Calavi, BeninSukhdev Singh, National Institute of Technology Patna, IndiaTing Su-Hie, Universiti Malaysia Sarawak, MalaysiaValeria Silva de Oliveira, Marinha do Brasil, Brazil
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.062 | 0.575 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.013 | 0.007 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.185 | 0.119 |
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".