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Record W7104422511 · doi:10.5281/zenodo.17549990

Exploring DataCite Metadata in OpenAlex

2025· article· en· W7104422511 on OpenAlexaff
Kyle Demes

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsOpenAlex
Fundersnot available
KeywordsDiscoverabilityMetadataVisibilityPresentation (obstetrics)Index (typography)Work (physics)Linked data

Abstract

fetched live from OpenAlex

OpenAlex, the world’s largest catalog of open research information, has added DataCite DOI metadata to its index to enhance the visibility and discoverability of datasets, preprints, awards, and other research outputs and activities. In this webinar, we will showcase the new integration, explain how users can work with OpenAlex to find and analyze DataCite DOIs and their relationships, and share tips for DataCite members about optimizing their metadata for discoverability. Speakers: Kyle Demes (COO, OurResearch) Maria Gould (Director of Strategic Programs and Partnerships, DataCite) A recording of the presentation can be found on the DataCite YouTube channel: https://youtu.be/hZaxHDBie4c?si=nO-k7MGRIPl2N74l

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesScholarly communication, Open science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0280.112
Open science0.0070.012
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.294
GPT teacher head0.337
Teacher spread0.043 · 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; both teacher heads agree on what is shown here.

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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