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Record W2553545048 · doi:10.1515/opar-2016-0016

From Science to Survival: Using Virtual Exhibits to Communicate the Significance of Polar Heritage Sites in the Canadian Arctic

2016· article· en· W2553545048 on OpenAlexaffabout
Peter Dawson, Richard Levy

Bibliographic record

VenueOpen Archaeology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsVisitor patternIndigenousArcticThe arcticVariety (cybernetics)National parkCultural heritageGeographyArchaeologyHistoryEnvironmental resource managementEcologyOceanographyComputer scienceEnvironmental scienceGeology

Abstract

fetched live from OpenAlex

Abstract Many of Canada’s non-Indigenous polar heritage sites exist as memorials to the Heroic Age of arctic and Antarctic Exploration which is associated with such events as the First International Polar Year, the search for the Northwest Passage, and the race to the Poles. However, these and other key messages of significance are often challenging to communicate because the remote locations of such sites severely limit opportunities for visitor experience. This lack of awareness can make it difficult to rally support for costly heritage preservation projects in arctic and Antarctic regions. Given that many polar heritage sites are being severely impacted by human activity and a variety of climate change processes, this raises concerns. In this paper, we discuss how virtual heritage exhibits can provide a solution to this problem. Specifically, we discuss a recent project completed for the Virtual Museum of Canada at Fort Conger, a polar heritage site located in Quttinirpaaq National Park on northeastern Ellesmere Island (http://fortconger.org).

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)0.004
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score0.806

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.056
GPT teacher head0.321
Teacher spread0.265 · 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

Citations13
Published2016
Admission routes2
Has abstractyes

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