Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.018 | 0.010 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.066 | 0.012 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".