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Making Design Review Interactive

2015· book-chapter· en· W2487291315 on OpenAlex
Rojin Vishkaie, Richard Levy

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

VenueAdvances in media, entertainment and the arts (AMEA) book series · 2015
Typebook-chapter
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAffordanceComputer scienceProcess (computing)VaguenessParticipatory designHuman–computer interactionDesign processCommunication designVisualizationCitizen journalismMultimediaEngineeringWork in processWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

As a synthesis, this paper offers the opportunity to rethink the status of current technologies within the design review process. It suggests the potential for transforming the complex participatory, communicative, and technical nuances of the design review process to coexist with the affordances of the new genre of digital media. Thus, this paper presents the final stage of an ongoing study that focuses on the design and evaluation of an interactive communication medium, called SketchBoard, for the design review process. Findings reveal that SketchBoard that embodies intelligent and intelligible behavior could potentially remedy the vagueness of visualization. This could further provide an insight into improving participatory communication and visualization around technical activities within the design review process using mobile interactive surfaces.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.783
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.005
Open science0.0010.001
Research integrity0.0000.001
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 head0.043
GPT teacher head0.311
Teacher spread0.268 · 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