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Record W2219329158 · doi:10.22230/src.2012v3n4a57

The Beginning, The Middle, and The End: New Tools for the Scholarly Edition

2013· article· en· W2219329158 on OpenAlexaffvenue
Stan Ruecker, Geoffrey Rockwell, Daniel Sondheim, Mihaela Ilovan, Jennifer Windsor, Mark Bieber, Luciano Frizzera, Omar Rodriguez, Kamal Ranaweera, Carlos Florentino, Stéfan Sinclair, Milena Radzikowska, Teresa Dobson, Ann Blandford, Sarah Faisal, Alejandro Giacometti, Susan Brown, Brent Nelson, Piotr Michura

Bibliographic record

VenueScholarly and Research Communication · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicDigital Humanities and Scholarship
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAffordanceComputer scienceSet (abstract data type)Reading (process)World Wide WebDigital humanitiesDigital libraryInterface (matter)Human–computer interactionLinguisticsProgramming language

Abstract

fetched live from OpenAlex

This article discusses a set of prototypes currently being designed and created by the Interface Design team of the Implementing New Knowledge Environments (INKE) project. These prototypes attempt to supplement the user experience in reading digital scholarly editions, by supporting a set of tasks that are straightforward in a digital environment but in a print edition would be sufficiently more difficult as to be prohibitive. We therefore offer these experimental prototypes as a collection of new affordances for the scholarly edition, although they may reasonably be extended, with some variation, to other kinds of digital text.

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)0.004
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.990
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0100.023
Open science0.0020.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0160.003

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 head0.244
GPT teacher head0.327
Teacher spread0.084 · 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
GenreMethods

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

Citations1
Published2013
Admission routes2
Has abstractyes

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