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Record W4234934705 · doi:10.1145/2931083

Demo hour

2016· article· en· W4234934705 on OpenAlexaff
Hsin-Liu Kao, Paul Johns, Asta Roseway, Mary Czerwinski, Lahiru Lakmal Priyadarshana, Victoria Porter, Juan Pablo Carrascal, Aaron Visser, Roel Vertegaal, Sarah Homewood, Gillian Smith, April Grow, Chenxi Liu, Lea Albaugh, Jen Mankoff, Jim McCann

Bibliographic record

Venueinteractions · 2016
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsQueen's University
Fundersnot available
KeywordsInteractivityWhite (mutation)Visual artsMultimediaComputer scienceSociologyArt

Abstract

fetched live from OpenAlex

Interactivity is a unique forum of the ACM CHI conference that showcases more than 50 cutting-edge demonstrations and inspirational interactive installations from the diverse group of researchers, designers, and artists that make up the CHI community. These works were chosen to engage audiences intellectually, imaginatively, and physically to create a critical discourse for the future of HCI. Julie R. Williamson, Amanda M. Williams, Sean White, and Cesar Torres, CHI 2016 Interactivity Chairs

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.704
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.7040.347

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 head0.022
GPT teacher head0.294
Teacher spread0.272 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2016
Admission routes1
Has abstractyes

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