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Record W4237024917 · doi:10.1145/2730891

Demo hour

2015· article· en· W4237024917 on OpenAlexaboutno aff
Max Rheiner, Thomas Tobler, Fabian Troxler, Seki Inoue, Keisuke Hasegawa, Yasuaki Monnai, Yasutoshi Makino, Hiroyuki Shinoda, Jules Françoise, Norbert Schnell, Riccardo Borghesi, Frédéric Bevilacqua, Tuncay Cakmak, Holger Hager

Bibliographic record

Venueinteractions · 2015
Typearticle
Languageen
FieldEngineering
TopicRobotics and Automated Systems
Canadian institutionsnot available
Fundersnot available
KeywordsHaptic technologyRoboticsEmerging technologiesEngineeringComputer scienceMultimediaHuman–computer interactionRobotArtificial intelligenceSimulation

Abstract

fetched live from OpenAlex

At SIGGRAPH 2014, the Emerging Technologies venue presented installations stemming from several fields, including displays, input devices, collaborative environments, robotics, haptics, and simulators. Of the 26 displayed installations at the conference (Vancouver, Canada, Aug. 10--14, 2014), we have selected the following four that highlight today's trends in technology and usage innovation. Thierry Frey, SIGGRAPH 2014 Emerging Technologies Chair

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 score0.757
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)0.7570.546

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 head0.041
GPT teacher head0.257
Teacher spread0.217 · 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
Published2015
Admission routes1
Has abstractyes

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