Bibliographic record
Abstract
Sometime between 1070 and 1077, Anselm, then prior of the monastery of Bec in Normandy, wrote to his friend Maurice, a former Bec monk residing at Christ Church, Canterbury, and asked him to seek out copies of various texts, including Bede's De temporibus and the Regula of St. Dunstan — presumably the Regularis concordia , the platform-document of the English Benedictine reform of the tenth century. Shortly thereafter, Anselm wrote again to Maurice, indicating that another text had been added to his desiderata: Should it come to pass that, with [Archbishop Lanfranc's] favor always embracing us, you return to us (as is expedient for you, and as you and I desire), bring with you what you will have copied of the Aphorisms . In the meantime, however, do as much of the text as you can without inconvenience to yourself, and then, if you are free, of the commentary, giving heed above all that whatever you will have brought with you has been corrected with the utmost diligence. If after your return any of it still remains to be done, and if Dom Gundulf is able to finish it through someone else, leave it to the person whom he designates. But it would be much better if Dom Gundulf were able to obtain by request the exemplar itself, so that it could be lent to me.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.041 | 0.009 |
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".