Bibliographic record
Abstract
Le Barou may l>e crowned with every poffible fuccc/s me of having complied with it.in this important objefl.It is the only means by This is lent to your excellency lor ywir govtni« which tlie current of Uiat valuable and lucrative trade ran be diverted from Canada to the United Stales, and it is the the lavag' the p»rt of the Indian tribes: We are h»Ppy Irani, that ever)-difpofition has been manifefted ou the part of the goveinment to encourage and fupport tnent.. God preferve your excellency many yean, .DON JOSEPH MONTEMATfcOaV only way to acquire fuch an afcendeucy over DON JOSEPH gt-mind, as to inl'ure a pacific difpofition on Cadi*, Nov. \tth t 1807 .-c .k. I,uii»n irihr«.We are happy to this ii'nwrunt objeft.[Wat.Int.1
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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.641 | 0.504 |
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".