Bibliographic record
Abstract
I wish, truly, that this was a skill in which I was not so well versed, that the call for commemoration was heard less often. Though if any man is owed tribute, it is Marcus Vipsanius Agrippa. We met studying at Apollonia, then both filled with the youthful vigor befitting the city’s namesake. Upon the death of my father, Divus Julius, I found in Agrippa a reliable and skilled ally. When my heart was filled with the unconquerable strength of just vengeance and my body was weakened by illness, it was he who stood by my side allowing Justitia’s sentence to be brought down upon Brutus and Cassius. Many we fought alongside at Philippi in time revealed themselves to be traitors to my father and the Roman people for whom we sought retribution. Agrippa and I together defeated Sextus Pompeius, who proved himself to be the lesser spawn of a great man. Here, my dear friend showed himself worthy of an honour which no man was bestowed before nor has been since, a golden crown ornamented by ships’ beaks.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".