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Record W1546203469

Introduction To Special Issue: FuturePlay Selected Papers

2009· article· en· W1546203469 on OpenAlexaffabout
Jennifer Jenson, Nis Bojin, Bill Kapralos

Bibliographic record

VenueLoading... · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsOntario Tech UniversitySimon Fraser UniversityYork University
Fundersnot available
KeywordsStudioMedia studiesLibrary scienceState (computer science)EntertainmentSelection (genetic algorithm)The artsArt historyOperations researchHistoryEngineeringSociologyArtVisual artsComputer scienceArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

This special issue of Loading… brings together a selection of the most highly reviewed papers from the annual ACM FuturePlay 2008 International Conference on the Future of Game Design and Technology conference that was held in Toronto, Ontario, November 3-5, 2008. The conference had over 170 attendees over the three days and included keynote addresses from Don Daglow (Founder/President/CEO of Stormfront Studios), Ben Sawyer (Co-founder of Digitalmill, Co-founder of the Serious Games initiative), Katie Salen (Parsons, the New School for Design), John Buchanan (Relic Entertainment), Ken Perlin (New York State University), and Jackie Copland (Electronic Arts).

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)0.008
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.242
Threshold uncertainty score0.808

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.004
Science and technology studies0.0030.001
Scholarly communication0.0130.006
Open science0.0020.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.2420.152

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 head0.006
GPT teacher head0.256
Teacher spread0.250 · 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
GenreEditorial

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
Published2009
Admission routes2
Has abstractyes

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