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Record W4312519954 · doi:10.1609/aiide.v9i1.12612

AIIDE-13 Organization

2013· article· en· W4312519954 on OpenAlexfundno aff
Gita Suthankar

Bibliographic record

VenueProceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBig Data and Business Intelligence
Canadian institutionsnot available
FundersSandia National LaboratoriesSimon Fraser UniversityBlekinge Tekniska HögskolaTeesside UniversityAalborg UniversitetUniversiteit van AmsterdamHeriot-Watt UniversityQueensland University of TechnologyUniversity of Southern CaliforniaUniversity of EssexUniversity of New South WalesUniversity of BoltonUniversity of DenverOregon State UniversityAir Force Institute of TechnologyUniversity of WashingtonLehigh UniversityRensselaer Polytechnic InstituteUniversity of Nevada, RenoNorthwestern UniversityDrexel UniversityNorth Carolina State UniversityUniversiteit van TilburgUniverzita Karlova v PrazeMoonshot Research and Development ProgramUniversidad Complutense de Madrid
KeywordsComputer science

Abstract

fetched live from OpenAlex

List of organizers of the Ninth Artificial Intelligence and Interactive Digital Entertainment Conference.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.312
Threshold uncertainty score0.446

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0030.000
Scholarly communication0.0090.002
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.6880.739

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 head0.055
GPT teacher head0.266
Teacher spread0.211 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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
Published2013
Admission routes1
Has abstractyes

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