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
Although mobile code systems typically employ link-time code verifiers to protect host computers from potentially malicious code, implementation flaws in the verifiers may still leave the host system vulnerable to attack. Compounding the inherent complexity of the verification algorithms themselves, the need to support lazy, dynamic linking in mobile code systems typically leads to architectures that exhibit strong interdependencies between the loader, the verifier, and the linker. To simplify verifier construction and provide improved assurances of verifier integrity, we propose a modular architecture based on the concept of proof linking. This architecture encapsulates the verification process and removes dependencies between the loader, the verifier, and the linker. We also formally model the process of proof linking and establish properties to which correct implementations must conform. As an example, we instantiate our architecture for the problem of Java bytecode verification and assess the correctness of this instantiation. Finally, we briefly discuss alternative mobile code verification architectures enabled by the proof-linking concept.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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