P12. You Transfer? UTransfer! - Evaluating year one of the UTransfer service provided by the University of Toronto Archives & Records Management Services
Bibliographic record
Abstract
This poster evaluates the challenges and successes of implementing UTransfer, a cloud-based transfer service to acquire digital records at the University of Toronto Archives & Records Management Services (UTARMS) using the open-source application ownCloud. The poster covers how this service fits into several ongoing projects at the University of Toronto Libraries, and the goal of building up digital preservation capacity within the Library. To achieve this, the poster highlights the workflows of the UTransfer service, the challenges encountered in the implementation and follow-up stages, and outcomes and paths forward for the coming years. The implementation of UTransfer has been a collaborative effort between multiple units within the university, including UTARMS, the University of Toronto Libraries Information Technology Services (ITS) department, and Scholars Portal. It is an example of leveraging existing tools to meet immediate challenges and move forward with the work of acquiring, preserving and making available our digital assets.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".