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The French and the Five Nations continue the War all Winter with various Success. The French burn a Captain of the Five Nations alive.

2017· book-chapter· en· W2789713880 on OpenAlexaboutno aff
Cadwallader Colden

Bibliographic record

VenueCornell University Press eBooks · 2017
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsFellCourageBeaverGeographyHistoryEconomic historyPolitical scienceDemographyAncient historyLawCartographySociologyEcology

Abstract

fetched live from OpenAlex

This chapter details the continuing war between the Five Nations and the French. The Five Nations maintained their incursions into Canada all winter. Forty of the Mohawks fell upon Fort Vercheres, and carried off twenty of the inhabitants. When the news reached Montreal, Mr. de Crizaei, with one hundred men of the regular troops, was sent in pursuit of them, who recovered most of the prisoners. The Count de Frontenac, being informed that a considerable party of the Five Nations hunted beaver on the neck of land between Cadarackui Lake and Lake Erie, resolved to demonstrate to them the strength and courage of the French.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.248
Threshold uncertainty score0.499

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0130.008
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0340.005

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 head0.016
GPT teacher head0.190
Teacher spread0.173 · 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
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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