Conservation survey, condition report and collections care proposal for the World War I portrait collection at State Records of South Australia
Bibliographic record
Abstract
This practical thesis project report contains a conservation survey, condition report and collections care proposal for the World War I portrait collection at State Records of South Australia. The plan prescribes immediate, short term and long term recommendations for the improvement of preservation techniques for the World War I collection. The paper also contains information and results gathered through the condition report of the collection sample and conservation survey. The survey investigated the current environment and storage facilities, access, security and disaster planning surrounding the collection. The paper also outlines the practices and methodologies of the applied thesis for both the conservation survey and condition report. The collection care proposal assesses current practices in order to provide State Records with accurate goals that offer flexible options. A detailed list of housing recommendations is included in the proposal; an advantages and disadvantages assessment if included for each option to help State Records better fit its needs and abilities in the future. Charts showing the results of the condition report and environmental assessment from the conservation survey are included in the appendix for further reference. This project is intended to draw attention to the urgent need for better preservation practices for the World War I portrait collection.
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 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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.102 | 0.036 |
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".