Leading the web in concurrent engineering: next generation concurrent engineering
Bibliographic record
Abstract
It is our great pleasure to welcome you to the 13th ISPE International Conference on Concurrent Engineering: Research and Applications, CE2006 being held in Antibes, France. The previous events were held in Dallas, Texas, USA (2005), Beijing, China (CE2004), Madeira Island, Portugal (CE2003), Cranfield, UK (CE2002), Anaheim, USA (CE2001), Lyon, France (CE2000), Bath, UK (CE99), Tokyo, Japan (CE98), Rochester, USA (CE97), Toronto, Canada (CE96), McLean, USA (CE95), Pittsburgh, USA (CE94). CE2007 and CE2008 are planned for Brazil and Australia, respectively. The CEXX conference series were launched by the International Society for Productivity Enhancement (ISPE) which, for more than a decade now, has constituted an important forum for international scientific exchange on concurrent engineering. These conferences attract more than a hundred researchers, industrials and students interested in the recent advances in concurrent engineering research and applications. Concurrent engineering is known as a strategic weapon to achieve industrial competitiveness by developing products better, cheaper and faster using multi-functional teamwork. The underlying focus of CE2006 Conference is in developing new methodologies, techniques and tools based on Web technologies required to support the key objectives of CE. For several years, with different technologies of information diffusion and sharing provided by the Web, new opportunities have appeared to improve the concurrent engineering approach. Bringing together concurrent engineering with Web technology and applications constitutes the strong and innovative points of the CE2006 Conference. The Web is not merely an immense book where people can search, browse, and view information. It is also a vast database that can allow computers to do more useful work. By developing a Web that holds information for both human and machine processing, people solve problems that would otherwise be too tedious or complex to solve (www.w3.org). The International Program Committee has decided to select the following major areas for CE2006: Keynote and invited papers Web services Interoperability and interfacing Collaborative, mobile and multimodal environment Semantic Enterprise, Semantic Web and ontologies Knowledge in CE Global Standardization Information Systems in CE Semantic indexing of documents Innovation and business strategies Design, manufacturing and services Cost engineering Education, social aspects and humanities Tools and applications vi We would like to thank all the authors for the high quality of their papers. We would like also to acknowledge the contribution of the key invited speakers, CE2006 International Program Committee and all session chairs in making a successful conference. We thank sincerely the members of the executive and organizing committees who helped in all aspects of organizing the conference (in particular Moisés Dutra Lima, Lionel Médini and Monique Simonetti). Last, we would like to gratefully acknowledge the institutional support and encouragement that we have received from our sponsors (in particular ISPE, INRIA, UCBL, W3C) and the funding received from Conseil Régional PACA, Ministère francais des affaires étrangères.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.016 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.008 |
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".