NOTERE’2006: nouvelles technologies de la répartition
Bibliographic record
Abstract
Les systemes et applications repartis ont fait emerger une problematique de recherche a la confluence des travaux sur les reseaux d'ordinateurs, l'algorithmique des travaux cooperatifs et les techniques de modelisation. Une communaute de recherche majoritairement francophone s'est formee pour relever ce defi la communaute NOTERE, dediee aux Nouvelles Technologies pour la Repartition et forte d'une conference internationale elle-meme denommee « NOTERE ». Dans le sillage des cinq premieres editions organisees a Pau (France), Montreal (Canada), Paris (France), Saidia (Maroc) et Gatineau (Canada), la conference NOTERE'06 s'est deroulee du 6 au 9 juin 2006 a l'ENSILA de Toulouse (France) dans le cadre d'un travail cooperatif de cette ecole d'ingenieurs avec le LAAS-CNRS (Toulouse) et l'ENST (Sophia-Antipolis). Le present ouvrage contient les actes de la sixieme edition de la conference NOTERE. La diversite de provenance des articles et la composition du comite de programme ont confirme le caractere international de la conference NOTERE. Les 32 articles ont ete retenus par le comite de programme pour leurs capacites novatrices. Ils anticipent et influencent le deploiement et les applications des futures technologies reseaux et de la repartition. La problematique visee par ce volume couvre la conception, la validation, le developpement et le deploiement des logiciels distribues et communicants. Les travaux presentes apportent des solutions pour la maitrise de la complexite architecturale et algorithmique. Les domaines d'application sont varies et couvrent les nouvelles applications Internet et les nouveaux services Web. Les contributions se repartissent en quatre categories. Elles portent sur les aspects methodologiques, les plates-formes et experimentations, le theme specifique de l'auto-adaptation et les aspects technologiques.
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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 | 0.017 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.026 | 0.011 |
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".