The Australian Recordkeeping Metadata Schema -- Version 1.0: Note from the Research Team
Bibliographic record
Abstract
The Australian Recordkeeping Metadata Schema," the major deliverable of an Australian collaborative research project published in Archivaria 48, the Australian Recordkeeping Metadata Schema (RKMS) was presented and discussed together with the conceptual framework within which this schema was developed.Included as an appendix to the article was a summary of the RKMS elements and qualifiers from the schema's final draft of 23 March 2000.This was the version of the RKMS available at the time of going to press.The release version of the RKMS, 31 May 2000, has a number of minor differences from the final draft, a result in the main of refinements to, and development of, metadata semantics.The most notable difference is in the "Relation" elements, RKMS08, RKMS019, RKMS30, and RKMS40, where the addition of two Value Components ("Related To" and "Type"), rather than utilizing an Element Qualifier, has provided a more effective means of representing relationships.This change has had a flow through effect to the final diagram given in the article, Figure 13 on page 25, with a minor adjustment required.A revised Figure 13 incorporating this change in the "Relation" element is provided below.This diagram now reflects a more direct specification of the type of relationship, in this case, Business Activity to Record Aggregation.Elsewhere in the RKMS there has been some further refinement of Element Qualifiers, in particular, the unique elements of the Records entity.The "Summary of the Elements and Qualifiers, Version 1.0, 31 May 2000" appears below.The full details of the project's findings and deliverable are available from the project Web site at: .
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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 | 0.031 | 0.079 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.015 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.028 | 0.017 |
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".