Bibliographic record
Abstract
Bu çalışma, Hicri I. asırdan V. asra kadar, Kur’ân
 lügatlerinin, doğuşundan gelişimine doğru nasıl bir seyir izlediğini kronolojik
 olarak örnekleriyle ve sözlük çeşitleriyle ele almaktadır. Çalışmamızın amacı
 bu sözlüklerin çıkış sürecindeki nedenlere de kısaca değinerek, türlerinin
 ilklerinden ve yenilik getirenlerinden örnekler vererek her bir sözlük türünün
 Kur’ân’ı anlamamızdaki işlevini ve onlardan nasıl daha iyi istifade
 edilebileceğini ortaya koymaya çalışmaktır. Bu çalışma Kur’ân sözlüğü sayılan
 veya Kur’ân sözlüğü olarak addedilebilecek çalışmalar olan Garîbü’l-Kur’ân,
 Vücûh ve’n-Nezâir ve Meâni’l-Kur’ân’ların ilk beş asırda telif edilenlerini,
 tarihi seyriyle beraber her bir türü özellikleriyle ve Kur’ân tefsirinde
 onlardan nasıl istifade edileceğiyle ilgili olarak örnekleriyle ele alacaktır.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.018 |
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".