Bibliographic record
Abstract
This chapter begins by describing how Ensign John Spoor of Captain Thomas De Witt's company led a seventeen-man fatigue party out from the fort on July 3, 1777, to cut blankets of sod for use in reinforcing and stabilizing the fort's earthen walls. While working, they came under attack by a party of around forty Indians sent out from Lieutenant Colonel Barrimore Matthew “Barry” St. Leger's force by Lieutenant Colonel Daniel Claus, deputy superintendent of the Seven Nations of Canada. Shortly after this incident, word of the devastating American evacuation of Fort Ticonderoga on July 6 reached Fort Stanwix. Just how Colonel Peter Gansevoort and the garrison reacted to the news is not known, but it must have given them pause as they contemplated the imminent attack on their fort. On July 30, an Indian rode up to the fort carrying a letter from the “Sachems of Caughnawaga and the Six Nations” at the Oneida Castle. The letter expressed their determination to remain at peace with the Americans and reported that the enemy force was then at the Three Rivers and that two detachments were to be sent ahead. About the same time, Captain De Witt arrived with his detachment from Fort Dayton, completely unifying the 3rd New York Regiment in one location for the first time.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.014 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.001 | 0.019 |
| Research integrity | 0.007 | 0.017 |
| Insufficient payload (model declined to judge) | 0.055 | 0.021 |
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".