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Record W2269703771

Enterprise application development in the cloud with IBM Bluemix

2014· article· en· W2269703771 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComputer Science and Software Engineering · 2014
Typearticle
Languageen
FieldComputer Science
TopicCloud Computing and Resource Management
Canadian institutionsIBM (Canada)
Fundersnot available
KeywordsIBMCloud computingComputer scienceJavaSoftware deploymentDowntimeVariety (cybernetics)Software engineeringService (business)Operating systemDevelopment environmentProcess (computing)Artificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

This workshop gave you an overview of IBM Bluemix and presented the enterprise application development process in the cloud environment. You have learned how to prototype an application and work with runtimes in the cloud environment. You also learned about boilerplates and services in IBM Bluemix. Participants used the Liberty profile to create a Java application and used services to extend the Java application's functions. Participants learned how to deploy applications using the blue-green, or zero downtime, deployment. Application monitoring and scaling were discussed as well as the charges for using Bluemix and how to estimate those charges. Participants acted as different personas; thereby using Bluemix as it would be used by a variety of clients. By the end of the workshop you have understood what Platform as a Service (PaaS) is and why to use Bluemix for cloud application development.

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.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.898
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.004
GPT teacher head0.176
Teacher spread0.172 · 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