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Record W1978958190 · doi:10.1145/2598784.2602788

CAMBRIA

2014· article· en· W1978958190 on OpenAlexafffund
Siniša Kolarić, Robert Woodbury, Halil Erhan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsSimon Fraser University
FundersNetworks of Centres of Excellence of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceGraphicsKey (lock)Forcing (mathematics)Set (abstract data type)Software engineeringSoftwareComputer graphicsHuman–computer interactionArtificial intelligenceProgramming languageComputer graphics (images)

Abstract

fetched live from OpenAlex

Software tools assist designers in their professional work, one key aspect of which is devising, evaluating, and choosing among multiple design alternatives. Yet, with few and limited exceptions, current tools handle just a single design model at a time, forcing users to adopt various ad-hoc strategies for dealing with multiple design alternatives. In this report we describe CAMBRIA, a multi-state prototype tool for simultaneously managing multiple 2D vector graphics models. Based on expert feedback, we propose an initial set of system design guidelines for building graphics editing systems capable of managing multiple, simultaneously available design solutions. We believe that these guidelines can be successfully applied in other areas of computing as well.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score1.000

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)0.0000.001

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 head0.210
Teacher spread0.205 · 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.

Study designTheoretical or conceptual
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
Published2014
Admission routes2
Has abstractyes

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