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Record W4315433245 · doi:10.16995/dscn.8080

Title Pending 8080

2023· article· fr· W4315433245 on OpenAlexvenueno aff
Chiara Azzaretti

Bibliographic record

VenueDigital Studies / Le champ numérique · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsnot available
Fundersnot available
KeywordsField (mathematics)Character (mathematics)Digital humanitiesWorld Wide WebComputer scienceLiteratureSociologyMultimediaLibrary scienceArt

Abstract

fetched live from OpenAlex

<strong>This is an accepted article with a DOI pre-assigned that is not yet published.</strong> For some literary scholars, the digital humanities can seem like unfamiliar and even intimidating territory. This article is a firsthand account by a newcomer to the field who contributed to the VESPACE social physics project in the summer of 2020. Through writing rules of video game character behavior based on eighteenth-century texts, the author gained a new understanding of the potential for digital initiatives to not only deepen "traditional" methods of textual analysis but to create exciting collaborative environments and projects.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.448
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.010

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 head0.063
GPT teacher head0.331
Teacher spread0.268 · 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 teacher head, 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

Citations0
Published2023
Admission routes1
Has abstractyes

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