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Record W2026632448 · doi:10.1145/505894.505911

Summary of the second ICSE workshop on web engineering

2001· article· en· W2026632448 on OpenAlexaboutno aff
Yogesh Deshpande, San Murugesan

Bibliographic record

VenueACM SIGSOFT Software Engineering Notes · 2001
Typearticle
Languageen
FieldComputer Science
TopicWeb Applications and Data Management
Canadian institutionsnot available
Fundersnot available
KeywordsEngineeringLibrary scienceWorld Wide WebWeb siteWeb engineeringComputer scienceWeb developmentWeb pageThe InternetWeb application security

Abstract

fetched live from OpenAlex

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).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.102
Threshold uncertainty score0.342

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0020.001
Scholarly communication0.0080.004
Open science0.0010.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.1020.082

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.

Opus teacher head0.014
GPT teacher head0.218
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations4
Published2001
Admission routes1
Has abstractyes

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