hpcng/singularity: Singularity 3.7.3
Bibliographic record
Abstract
Singularity 3.7.3 is a security release. We recommend all users upgrade to this version. Security Related Fixes CVE-2021-29136: A dependency used by Singularity to extract docker/OCI image layers can be tricked into modifying host files by creating a malicious layer that has a symlink with the name "." (or "/"), when running as root. This vulnerability affects a <code>singularity build</code> or <code>singularity pull</code> as root, from a docker or OCI source. Thanks / Reporting Bugs Thanks to our contributors for code, feedback and, testing efforts! As always, please report any bugs to: https://github.com/hpcng/singularity/issues/new If you think that you've discovered a security vulnerability please report it to: security@sylabs.io Have fun! Downloads Please use the <code>singularity-3.7.3.tar.gz</code> download below to obtain and install Singularity 3.7.3. The GitHub auto-generated 'Source Code' downloads do not include required dependencies etc.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.397 | 0.428 |
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".