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Record W7016246785

What We Have Learned: A Retrospective on Parks Canada War of 1812 Military Sites Archaeology

2017· article· en· W7016246785 on OpenAlexfundaboutno aff

Bibliographic record

VenueThe Open Repository - Binghamton (Binghamton University) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsnot available
FundersParks Canada
KeywordsNucleofectionTSG101HyporeflexiaGestational periodDiafiltrationProteogenomicsPretext
DOInot available

Abstract

fetched live from OpenAlex

Over the past five decades, Parks Canada archaeology has advanced the understanding of War of 1812 sites in Ontario. Delineation of the original 1796 traces at Fort George and Fort Malden provide enhanced appreciation of their transformation from defensible supply stations to works of greater strength. Investigations at Forts Mississauga, Henry, and Wellington illustrate how British Royal Engineers rethought defense, varying designs as the war progressed. Fort Wellington also demonstrates British engineers willingness to stray from Vauban-influenced systems by adopting the bastion-less trace in their later works. Excavations at Fort George illustrate American use of entrenchments as an expedient means of perimeter defense. In addition to site design, alterations, and future archaeological potential, excavations also reveal insights about occupation and activities: from raucous dinner parties to evocative caches of flints and buttons. In hindsight, the usefulness of employing a long-term/small-scale cultural resource management approach to Ontario military sites archaeology is briefly evaluated along with recommendations for future study.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.400

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.010
Science and technology studies0.0150.005
Scholarly communication0.0050.002
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.037
GPT teacher head0.270
Teacher spread0.233 · 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 designObservational
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

Citations1
Published2017
Admission routes2
Has abstractyes

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