MétaCan
Menu
Back to cohort

Integrating SaaS and SaaP with Dew Computing

2016· article· en· W2544713694 on OpenAlexaff
Yingwei Wang, David J. LeBlanc

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCloud Computing and Resource Management
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsSoftware as a serviceCloud computingComputer scienceSoftware engineeringSoftwareSoftware developmentWorld Wide WebOperating system

Abstract

fetched live from OpenAlex

Software as a Service (SaaS) is one of the major service models of cloud computing and a new software delivery model, in this software delivery model, software is hosted centrally, is licensed to users on subscription basis, and typically is accessed by users through a Web browser. Before SaaS was introduced, the traditional software delivery model was Software as a Product (SaaP): software was sold to users and installed in users local computers. In this paper, we discuss the advantages and disadvantages of SaaS and SaaP, and suggest a new software delivery model that is an integration of SaaS and SaaP. Dew computing can be used to integrate SaaS and SaaP. This new software delivery model has some great features.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.892
Threshold uncertainty score0.203

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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

Citations18
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicCloud Computing and Resource ManagementFrench-language works237,207