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
Abstract SCOOP is a concurrent programming language with a new semantics for contracts that applies equally well in concurrent and sequential contexts. SCOOP eliminates race conditions and atomicity violations by construction. However, it is still vulnerable to deadlocks. In this paper we describe how far contracts can take us in verifying interesting properties of concurrent systems using modular Hoare rules and show how theorem proving methods developed for sequential Eiffel can be extended to the concurrent case. However, some safety and liveness properties depend upon the environment and cannot be proved using the Hoare rules. To deal with such system properties, we outline a SCOOP Virtual Machine (SVM) as a fair transition system. The SVM makes it feasible to use model-checking and theorem proving methods for checking global temporal logic properties of SCOOP programs. The SVM uses the Hoare rules where applicable to reduce the number of steps in a computation.
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 | 0.001 | 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