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
Recursion is a programming technique in which a solution can be expressed by a subroutine invoking itself either directly or indirectly. Many problems can be expressed simply using a recursive approach, however one of the drawbacks of using recursion is that it requires a stack, and often one does not know how much stack space is needed to obtain a recursive result. Stack overflow often results in spectacular failure with strange, often unrepeatable behaviour. Paraffin is a suite of generic units that can add parallelism to iterative and recursive problems. Some of the generics involve a load balancing technique described as "work-seeking". It was found that the recursive work seeking algorithm could be extended to also provide stack safety whereby the generics monitor the amount of remaining stack space and avoid stack overflow using a technique similar to load balancing. The stack safety feature also makes it attractive to consider Paraffin for use with code destined for execution on a single core. This paper describes how the recursive work-seeking algorithm was extended to provide the stack-safety feature, and then goes on to report some performance results using the generics.
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 | 0.002 | 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