Vers un modèle de composition de services web avec propriétés transactionnelles
Bibliographic record
Abstract
The development of new services by composition of existing ones has gained considerable momentum as a means of integrating heterogeneous applications and realising business collaborations. Services that enter into compositions with other services may have transactional properties, especially those in the broad area of resource management (e.g. booking services). These transactional properties may be exploited in order to derive composite services which themselves exhibit certain transactional properties. This paper presents a model for composing services that expose transactional properties and more specifically, services that support tentative holds and/or atomic execution. The proposed model is based on a high-level service composition operator that produces composite services that satisfy specified atomicity constraints. The model supports the possibility of selecting the services that enter into a composition at runtime, depending on their ability to provide resource reservations at a given point in time and taking into account user preferences.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".