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Record W3176329926 · doi:10.4000/jtei.4352

Distributed Text Services (DTS): A Community-Built API to Publish and Consume Text Collections as Linked Data

2023· article· en· W3176329926 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Text Encoding Initiative · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicDigital Humanities and Scholarship
Canadian institutionsTyndale University
Fundersnot available
KeywordsJSONComputer scienceSerializationMetadataXMLInteroperabilityWorld Wide WebKey (lock)Information retrievalDatabaseProgramming languageOperating system

Abstract

fetched live from OpenAlex

This paper presents the Distributed Text Service (DTS) API Specification, a community-built effort to facilitate the publication and consumption of texts and their structures as Linked Data. DTS was designed to be as generic as possible, providing simple operations for navigating collections, navigating within a text, and retrieving textual content. While the DTS API uses JSON-LD as the serialization format for non-textual data (e.g., descriptive metadata), TEI XML was chosen as the minimum required format for textual data served by the API in order to guarantee the interoperability of data published by DTS-compliant repositories. This paper describes the DTS API specifications by means of real-world examples, discusses the key design choices that were made, and concludes by providing a list of existing repositories and libraries that support DTS.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.168
GPT teacher head0.312
Teacher spread0.144 · 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