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Record W3154303944 · doi:10.24908/iqurcp.10650

9. Piecing Together Monumental Sites of History

2018· article· en· W3154303944 on OpenAlexvenueno aff
Kelsey Jennings

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Tourism and Spaces
Canadian institutionsnot available
Fundersnot available
KeywordsVariety (cybernetics)Key (lock)World Wide WebGeospatial analysisQueen (butterfly)Library scienceTask (project management)HistoryVisual artsComputer scienceArtGeographyEngineeringCartography

Abstract

fetched live from OpenAlex

Uncovering some of the United Kingdoms most fascinating historical sites, this interactive digital website puts on display one of the newest collections in Queen’s W.D. Jordan Special Collections Library. Using geospatial location technology and a variety of digital humanities concepts, the project undertook the task of mapping over 700 architectural guidebooks from across the United Kingdom. A key driving factor in the creation of the site was the challenge of making collections more accessible to students; encouraging the use of the wide range of the primary source material. The website conjoins the large guidebook collection with literature found in the Schulich-Woolf rare book collection. Through a thorough investigation of the existing literature in the library, this platform connects the plethora 20th-century guidebooks with the many rare 18th, 19th, and 20th-century antiquity books featured in the Schulich-Woolf collection. Through an accessible platform, students are now able to view the guidebook collection, while being able to access key resources for further research into key pieces of British history and identity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.005
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.136
GPT teacher head0.400
Teacher spread0.264 · 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 teacher head, not a consensus.

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
Published2018
Admission routes1
Has abstractyes

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