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Record W2035490936 · doi:10.1629/2431

The need and drive for open data in biomedical publishing

2011· article· en· W2035490936 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSerials The Journal for the Serials Community · 2011
Typearticle
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsnot available
FundersGenome CanadaNational Institutes of HealthNational Science FoundationCancer Research UKWellcome TrustMedical Research CouncilWellcome
KeywordsOpen dataOpen scienceData sharingScrutinyScholarly communicationPublishingReuseData publishingComputer scienceOpen researchData scienceService (business)World Wide WebPolitical scienceBusinessEngineering

Abstract

fetched live from OpenAlex

The concept of open data goes beyond making data freely available. Data must also be free to reuse and build upon without legal or technical impediments. Funder and journal policies for data sharing and the growing open science movement are helping open data to spread across biomedical sub-disciplines. Editors should embrace open data to ensure that their decisions can stand up to close scrutiny; journals need open data to help them fulfil their stated goals, and publishers should utilize open data and data publication to serve the growing sector of the scientific community requiring it as a service, and to continue developing novel forms of scholarly communication in an increasingly data-intensive scholarly communication environment.

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)0.106
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Open science
Consensus categoriesMetaresearch, Scholarly communication, Open science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.724
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1060.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0190.037
Open science0.0400.023
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.441
GPT teacher head0.438
Teacher spread0.002 · 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