Bibliographic record
Abstract
Abstract Flash storage media such as memory cards and USB flash drives are now commonly used to transfer and store information. However, little is known about the long-term stability of this type of media and this is a concern for archives and other institutions as they begin to receive content stored on these devices. In this study, the stabilities of a variety of different flash media were examined. The evaluation was performed by using accelerated ageing at 85 °C and 85 % relative humidity (RH) and 125 °C for ageing intervals up to 2000 hours. Measurements were also performed on samples previously subjected to accelerated ageing and then naturally aged for five years to verify the results from the accelerated ageing experiments. Overall, the stability of flash media was very good. For many of the samples, no read errors were encountered after accelerated or natural ageing. However, for several of the high capacity flash card samples and USB flash drives, significant decreases in read speed were noted. This can be problematic because it will eventually lead to read errors. It was established that for the USB samples this instability was likely attributed to the use of the less stable TLC (triple-level cell) memory chip.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".