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Record W2149931362 · doi:10.1109/mcg.2009.78

CoCoNutTrix: Collaborative Retrofitting for Information Visualization

2009· article· en· W2149931362 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

VenueIEEE Computer Graphics and Applications · 2009
Typearticle
Languageen
FieldComputer Science
TopicData Visualization and Analytics
Canadian institutionsUniversity of CalgaryPetro-Canada
Fundersnot available
KeywordsComputer scienceVisualizationRetrofittingData visualizationInformation visualizationDomain (mathematical analysis)Data scienceSocial network analysisHuman–computer interactionWorld Wide WebData miningEngineeringSocial media

Abstract

fetched live from OpenAlex

In this paper, the authors retrofitted a version of NodeTrix, a single-user graph visualization environment based on the InfoVis toolkit, to support multiple independent mice. The resulting low-cost environment was called CoCoNutTrix (Colocated Collaborative NodeTrix). Then, it was assessed how analysts viewed CoCoNutTrix and whether it effectively supported collaborative data analysis among domain experts using real data sets for social-network analysis. Our goal is to refine and expand our knowledge about retrofitting and hence designing colocated collaborative- visualization systems.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.296
Teacher spread0.282 · 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