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Record W2903285790 · doi:10.1145/3281505.3281600

Hamlet

2018· article· en· W2903285790 on OpenAlexaff
Krzysztof Pietroszek, Christian Eckhardt, Liudmila Tahai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHuman Motion and Animation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSoliloquyHAMLET (protein complex)GestureComputer scienceMotion (physics)ChoreographyDanceHuman–computer interactionArtArtificial intelligenceComputer graphics (images)Visual artsLiterature

Abstract

fetched live from OpenAlex

We present "Hamlet", a prototype implementation of a virtual reality experience in which a player takes on a role of the theater director. The objective of the experience is to direct Adam, a virtual actor, to deliver the best possible performance of Hamlet's famous "To be, or not to be" soliloquy. The player interacts with Adam using voice commands, gestures, and body motion. Adam responds to acting directions, offers his own interpretations of the soliloquy, acquires the choreography from the player's body motion, and learns the scene blocking by following the player's pointing gestures.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.895
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1050.021

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 head0.007
GPT teacher head0.192
Teacher spread0.184 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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