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Record W7079472655 · doi:10.7910/dvn/3xdmnf

APCs of 2,228 journals where NIH-funded authors published in 2025

2025· dataset· en· W7079472655 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

VenueHarvard Dataverse · 2025
Typedataset
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsUniversité de MontréalSimon Fraser UniversityUniversity of Ottawa
Fundersnot available
KeywordsPublishingBibliometricsMEDLINEImpact factorSet (abstract data type)

Abstract

fetched live from OpenAlex

This dataset includes the top 2,228 journals publishing NIH-funded research between January and July 2025. For each journal, it provides bibliographic details (title, ISSNs, publisher), 2025 publication counts acknowledging NIH support (based on Dimensions data from 24.07.2025), open access status (gold, hybrid, diamond, S2O), publisher type (for profit, not for profit), and its current 2025 Article Processing Charge (APC). The dataset also includes calculations to project the effect of proposed NIH policy scenarios to cap allowable grant spending on APCs at $2,000, $3,000, or $6,000. This dataset supports analyses of NIH-funded publication fees by journal, publisher, OA status and business models. We encourage its use in responding to the NIH's Request for Information.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0050.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.019
GPT teacher head0.263
Teacher spread0.244 · 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