MétaCan
Menu
Back to cohort
Record W2003484266 · doi:10.1109/icsm.2010.5609696

2D and 3D visualizations in WikiDev2.0

2010· article· en· W2003484266 on OpenAlexaff
Marios Fokaefs, Diego Serrano, Brendan Tansey, Eleni Stroulia

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsVisualizationComputer scienceZoomInteractivityHuman–computer interactionSoftwareSoftware visualizationInformation visualizationData visualizationProcess (computing)World Wide WebSoftware developmentComponent-based software engineeringEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Several types of 3D software visualizations have been developed to communicate information about the products of a software project and, sometimes, the development process itself. These visualizations have been limited in the degree of interactivity they enabled (primarily panning and zooming) and in their accessibility (since in most cases they assumed a particular client platform). In this paper we discuss our 3D visualization of the data collected and extracted in our collaborative software-development platform WikiDev2.0, developed in the Open Wonderland virtual world. The visualization adopts a city metaphor, similar to earlier work, but advances the state of the art by providing a web-accessible distributed 3D environment where multiple users can explore the same project. In this paper we discuss this visualization, which we call WikiDev3D, and we report on our preliminary findings about its effectiveness against the more traditional visualization of the original WikiDev2.0 tool.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.585
Threshold uncertainty score0.120

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 head0.012
GPT teacher head0.296
Teacher spread0.284 · 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 designObservational
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

Citations7
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicSoftware Engineering ResearchFrench-language works237,207