Digital Library Federation (DLF) Aquifer Project
Bibliographic record
Abstract
In January 2005, the Digital Library Federation (DLF) renewed its commitment to developing a distributed open digital library by assigning a full time project director to lead the initiative. Called DLF Aquifer to symbolize the pooling of content into a community resource, and the piping or siphoning of content to meet specific needs, the collaboration amongst a subset of DLF member libraries has produced standards, reports, and prototypes over the past year. The work was accomplished through four working groups focused on services, technology/architecture, metadata, and collections, with additional participation by library staff at DLF Aquifer institutions. One prototype was created through a collaboration that extended beyond DLF membership. This project update highlights "Phase I" DLF Aquifer deliverables and provides a brief overview of future plans. Additional details, including the DLF Aquifer business plan, working group rosters, and mode of operation can be found on the DLF Aquifer web site. A list of participating institutions is included here, as an appendix.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.036 | 0.009 |
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".