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Record W3211162394 · doi:10.5281/zenodo.3557012

Web Service Dataset

2019· dataset· en· W3211162394 on OpenAlexaff
Eyhab Al‐Masri

Bibliographic record

VenueFigshare · 2019
Typedataset
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsComputer scienceWorld Wide WebWeb serviceDatabaseWeb applicationService (business)Information retrievalBusiness

Abstract

fetched live from OpenAlex

The QWS Dataset ver 1.0 includes a set of 365 web services and their Quality of Web Service (QWS) measurements that were conducted during the year of 2008 using our web Service Broker (WSB) framework. Each row in this dataset represents a Web service and its corresponding nine QWS measurements (separated by commas). The first nine elements are QWS metrics that were measured using multiple Web service benchmark tools over a six-day period. The QWS values represent averages of the measurements collected during that period. The last two parameters represent the service name and reference to the WSDL document.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0070.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0850.110

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 head0.035
GPT teacher head0.270
Teacher spread0.235 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations1
Published2019
Admission routes1
Has abstractyes

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