Bibliographic record
Abstract
Abstract Blackburn Museum and Art Gallery has a nationally significant coin collection, thanks mainly to two bequests in the early twentieth century. The donation by R. E. Hart, a local industrialist, was made along with all his accompanying notes and books. This collection offers unique insights into the habits and aims of Hart as a numismatist, his wider network and the intellectual community of collecting. Understanding Hart’s processes of acquisition, and his role as a learned society member and customer of major auction houses supplies the outlines of a shared endeavour that, in the early twentieth century, shaped social and personal, as well as economic and cultural identities. Collections and collecting like Hart’s were also fundamental in creating the resources and structures for numismatic study today, offering a reminder of the importance of preserving and understanding inclusive environments of knowledge curation, as well as context for the collections underpinning much current research.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.010 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.135 | 0.034 |
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".