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Record W2991175422 · doi:10.14236/ewic/eva2014.0

Electronic Visualisation and the Arts (EVA 2014) - Index

2014· article· en· W2991175422 on OpenAlexaboutno aff
Kia Ng, Jonathan P. Bowen, Sarah McDaid

Bibliographic record

VenueElectronic workshops in computing · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
Fundersnot available
KeywordsThe artsVisualizationVisual artsLibrary scienceIndex (typography)SociologyComputer scienceArtWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

The Electronic Visualisation and the Arts London 2014 conference (EVA London 2014) is co-sponsored by the Computer Arts Society (CAS) and British Computer Society (BCS) - the Chartered Institute for IT, of which the CAS is a specialist group. 2014 marks the 25th Anniversary of EVA London. Over the last two decades, the EVA conference has established itself as one of London’s most innovative and interdisciplinary conferences in the field of digital visualisation. The papers in this volume touch on music, performance, electronic art, imaging technology, medical visualisation, museums and their collections, virtual communities, landscape visualisation, augmented reality, 3D imaging, interfaces, and enhanced reality, as well as other areas. The latest research by established scholars, early career researchers, practitioners, and students can be found here. For more information about EVA 2014, visit www.eva-london.org or search on Twitter for EVALondonConf. 2014 marks the 25th Anniversary of EVA London! Over the last two decades, the EVA London conference on Electronic Visualisation and the Arts has established itself as one of the United Kingdom’s most innovative and interdisciplinary conferences. It brings together a wide range of research domains to celebrate a diverse range of interests with a specialised focus on visualisation. The EVA London 2014 conference presents a wide spectrum of papers, presentations, demonstrations, a research workshop and a special pre-conference event: “V&A Digital Futures meets EVA London”. It is a forum where the sciences, arts, humanities, and performance, are equally at home. EVA London 2014 presents 76 papers and abstracts from 24 countries, by researchers inside and outside academia, from graduate artists, PhD students, seasoned industry professionals, established scholars, and senior researchers, who value EVA London for its interdisciplinary community. This year, the conference features three keynote speakers: Prof. Sally-Jane Norman from the Attenborough Centre for the Creative Arts, University of Sussex; Dr Lizzie Jackson from Ravensbourne; and Tom Wickham-Jones from Wolfram Research. The proceedings has resulted from a highly selective peer review process, fitting as many excellent submissions as possible into the limited timetable of the conference. The papers in this volume touch on music, performance, electronic art, imaging technology, medical visualisation, museums and their collections, virtual communities, landscape visualisation, augmented reality, 3D imaging, interfaces, and enhanced reality, as well as other interdisciplinary areas. EVA London is part of a larger network of EVA international conferences. In the past twenty years, EVA events have been held in Athens, Beijing, Berlin, Brussels, California, Cambridge (both UK and USA), Dallas, Delhi, Edinburgh, Florence, Gifu (Japan), Glasgow, Harvard, Jerusalem, Kiev, Laval, London, Madrid, Montreal, Moscow, New York, Paris, Prague, Thessaloniki, and Warsaw. Further venues for EVA conferences are very much encouraged by the EVA community.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.394
Threshold uncertainty score0.865

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.007
Science and technology studies0.0020.001
Scholarly communication0.0180.009
Open science0.0010.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.3940.198

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 head0.027
GPT teacher head0.243
Teacher spread0.216 · 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.

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

Citations3
Published2014
Admission routes1
Has abstractyes

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