Bibliographic record
Abstract
George Timmins' letters posed few issues of transcription, although the passage of time and use occasionally compromised legibility. Save for those written before Timmins' departure overseas, the wartime letters are written in pencil and on poor-quality paper, which is showing signs of deterioration, notably along the folds. Where the original text fails to provide the date and year of entry, they appear here within square brackets. The editor has arrived at these dates by correlating internal evidence with other sources. The original punctuation, spelling, and paragraphing of this edition are George Timmins' own. The interventions of the military censors are indicated by the use of [censored] inserted into the text. If words have been censored but are still legible, these have been identified by an endnote. Timmins frequently added a postscript, either at the head of a letter or more usually at the end, depending on space. Sometimes, however, he did not use the conventional "p.s." to signal a postscript. In transcribing his letters, the postscripts have been left where
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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.160 | 0.136 |
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".