Audit and Certification of Trustworthy Digital Repositories: Recommended Practice, Issue 1
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This document is a technical Recommendation to use as the basis for providing audit and certification of the trustworthiness of digital repositories. It provides a detailed specification of criteria by which digital repositories shall be audited. The OAIS Reference Model contained a roadmap which included the need for a certification standard. The initial work was to be carried out outside CCSDS and then brought back into CCSDS to take into the standard. \nIn 2003, Research Libraries Group (RLG) and the National Archives and Records Administration (NARA) created a joint task force to specifically address digital repository certification. That task force published Trustworthy Repositories Audit & Certification: Criteria and Checklist (TRACâreference [B3]), on which this Recommended Practice is based. Through the process of normal evolution, it is expected that expansion, deletion, or modification of this document may occur. This Recommended Practice is therefore subject to CCSDS document management and change control procedures, which are defined in the Procedures Manual for the Consultative Committee for Space Data Systems. Current versions of CCSDS documents are maintained at the CCSDS Web site: http://www.ccsds.org/
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.006 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it