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
Edited by Lynne Truss. (Pp 209; hardback.) Gotham Books (Penguin Group) New York, 2003, ISBN 1-592-40087-6. Most writers punctuate. Not everyone punctuates correctly. Few punctuate well. Lynne Truss’s best-seller, Eats, Shoots & Leaves is certain to raise each reader’s writing one large notch. As a bonus, it is a great read; witty, caustic, and wise. If only I had written this review before the book’s meteoric climb to the top best-seller lists (where it remains). Had I done so this would not now be in the company of the hundreds of other reviews, mostly positive, ranging from warm praise to exuberance. Only a few—notably that by Louis Menand in the New Yorker (June 28, 2004, pp 102–4)—are profoundly critical. (Methinks Menand must be a sourpuss.) This is a book to be read for fun and profit. If all contributors …
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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