Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper aims to work toward a proper understanding of the role of preverbal ge- in Old English (henceforth OE) and its disappearance in the course of Middle English. This prefix is reminiscent of its cognates in Modern German and Dutch (also written ge-) in its distribution, but even a cursory examination of the details reveals it to be quite distinct, as we will see. The proper characterization of that distribution, and of its diachronic development, has proven to be extremely difficult. I have thus carried out a large-scale corpus study using the York-Toronto-Helsinki parsed corpus of Old English prose (Taylor et al. 2003) and the Penn-Helsinki parsed corpus of Middle English, 2nd ed. (Kroch & Taylor 1999). This paper will report the results of the first phase of the project, involving patterns in the data that could be identified primarily on the basis of automatic searches in the corpora.
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.
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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it