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Record W2021886098 · doi:10.1109/c5.2012.9

Orca: A Single-Language Web Framework for Collaborative Development

2012· article· en· W2021886098 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWeb Applications and Data Management
Canadian institutionsBC Research (Canada)
Fundersnot available
KeywordsComputer scienceWorld Wide WebWeb developmentHypertextSmalltalkServer-sideWeb applicationObject-oriented programmingWeb serviceProgramming language

Abstract

fetched live from OpenAlex

In the last few years, the Web has been established as a platform for interactive applications. However, creating Web applications involves numerous challenges since the Web has been created to serve static content. In particular, the separation of the client- and the server-side, being only connected through the unidirectional Hypertext Transfer Protocol, forces developers to apply two programming languages including different libraries, conventions, and tools. Developers create expert knowledge by specializing on a few of all involved technologies. Consequently, the diverse knowledge of team members makes collaboration in Web development laboriously. We present the Orca framework that allows developers to work collaboratively on client-server applications in a single object-oriented programming language. Based on the Smalltalk programming language, full access to existing libraries, and a bidirectional messaging abstraction, Orca provides a consistent environment that supports common idioms and patterns in client- and server-side code. It reduces expert knowledge and the number of development tools and, thus, facilitates the collaboration of Web developers.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.976
Threshold uncertainty score0.270

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 head0.034
GPT teacher head0.284
Teacher spread0.250 · 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

Quick stats

Citations1
Published2012
Admission routes1
Has abstractyes

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