Bibliographic record
Abstract
Clustered Objects (COs) [1] have been proven to be an effective abstraction for improving scalability of systems software [2, 3]. But can we devise a programming model that would allow COs to live outside the specialized environments of these operating systems and still provide benefit? This paper presents an overview of SCOPE (Scalable COs with Portability Events), a prototype user-level library derived from the original implementation of COs in the K42 OS. Our initial results indicate that not only do the benefits of COs hold, but that the notion of a "portability event", responsible for maintaining the runtime environment of COs, provides a powerful programming model that will enable COs to be seamlessly transplanted into systems beyond K42. This paper overviews this programming model, provides details and preliminary results from its prototype implementation in SCOPE, and provides motivation to consider simple language mechanisms to further support portability events and this programming model in general.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".