Summary of the second ICSE workshop on web engineering
Bibliographic record
Abstract
The series of workshops on Web Engineering started in 1998 with the World Wide Web Conference WWW7 in Brisbane, Australia, and has continued with WWW8 (Toronto, 1999) and WWW9 (Amsterdam, 2000). The first such workshop with the International Conference on Software Engineering (ICSE) took place in 1999 in Los Angeles. The second workshop was held on 4-5 June 2000 in Limerick, Ireland and attracted about 30 participants.The main purpose behind these workshops is to share and pool the collective experience of people, both academics and practitioners, who are actively working on Web-based systems.This workshop consisted of two keynote addresses, 11 contributed papers and two sessions of open discussions. The call for papers elicited 18 submissions of which 11 were accepted after peer reviews. The papers presented at the workshop appear in the book Web Engineering (San Murugesan and Yogesh Deshpande (eds.), LNCS, Springer-Verlag, 2000).
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.102 | 0.082 |
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".