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Record W4391625392 · doi:10.1002/9781394260348.ch2

War for Independence

2019· other· en· W4391625392 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicColonialism, slavery, and trade
Canadian institutionsnot available
Fundersnot available
KeywordsIndependence (probability theory)Political scienceMathematicsStatistics

Abstract

fetched live from OpenAlex

With Americans turning against the British Empire, the Continental Congress met in the city of Philadelphia. James Monroe, an 18-year-old student at the College of William and Mary, left his books and joined the Third Virginia Regiment in early 1776. The Continental Army stood at a crossroads in 1777. British General John Burgoyne with 8,000 troops advanced southward from Canada to the Hudson River. Jeffrey Brace, who was also known as Boyrereau Brinch, served with comrades from Stanford to Hackensack. Born in western Africa around 1742, he was captured at age 16 and shipped to the Caribbean island of Barbados. The Franco-American alliance of 1778 offered prospects for foreign aid, coordinated campaigns, and naval operations. A French declaration of war on Great Britain that year was followed by a Spanish declaration in 1779 and by a Dutch declaration in 1780.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.155
Threshold uncertainty score0.519

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.002
Scholarly communication0.0050.003
Open science0.0010.007
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.1550.065

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.

Opus teacher head0.025
GPT teacher head0.327
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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