Bibliographic record
Abstract
İstanbul Teknik Üniversitesi, Türkiye Istanbul Technical University, Turkey Reutlingen Üniversitesi, Almanya Reutlingen University, Germany Concordia Üniversitesi, Kanada Concordia University, Canada İstanbul Üniversitesi, Türkiye Istanbul Technical University, Turkey Çanakkale Onsekiz Mart Üniversitesi, Türkiye Çanakkale Onsekiz Mart University, Turkey Dokuz Eylül Üniversitesi, Türkiye Dokuz Eylul University, Turkey Tennessee Üniversitesi, ABD Tennessee University, USA Akdeniz Üniversitesi, Türkiye Akdeniz University, Turkey Friedrich-Alexander Üniversitesi, Almanya Friedrich-Alexander University, Germany Selanik Aristotle Üniversitesi, Yunanistan Aristotle University of Thessaloniki, Greece Queensland Teknoloji Üniversitesi, Avustralya Queensland University of Technology, Australia Curtin Üniversitesi, Avustralya Curtin University,Australia Azerbeycan Bilimler Akademisi, Azerbaycan Azerbaijan Academy of Sciences, Azerbaijan Dokuz Eylül Üniversitesi, Türkiye Dokuz Eylul University, Turkey Karadeniz Teknik Üniversitesi, Türkiye Karadeniz Technical University, Turkey Seul Ulusal Üniversitesi, Güney Kore Seoul National University, Korea Orta Doğu Teknik Üniversitesi, Türkiye Middle East Technical University, Turkey Gazi Üniversitesi, Türkiye Gazi University, Turkey Environment Canada, Kanada Environment Canada, Canada
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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; both teacher heads agree on what is shown here.
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".