Bibliographic record
Abstract
In this paper a , we present a dynamic semantics for the Java Virtual Machine Language (JVML).The semantics is specified in an operational style according to the syntactic structure of JVML programs.In order to ascribe meanings to threading, the semantics is made small-step and is structured in two layers: The first layer consists of judgements that capture the semantics of sequential JVML programs in isolation.The second layer consists of judgements that capture the parallel execution of JVML threads.The semantics presented in this paper is a faithful and formal transcription of JVML specification as described in [1].Besides, we provide full account details for the most technical and tricky aspects of JVML such as multi-threading, synchronization, method invocations, exception handling, object creation, object's fields manipulation, stack manipulation, local variable access, modifiers, etc.The presented semantics is, to the best of our knowledge, the first dynamic semantics of JVML that provides semantics for that many features within the same framework.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".