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Record W2728933342 · doi:10.3897/rio.3.e14672

Data Management Plan: IDRC Data Sharing Pilot Project

2017· article· en· W2728933342 on OpenAlexfundno aff
Cameron Neylon

Bibliographic record

VenueResearch Ideas and Outcomes · 2017
Typearticle
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsData management planData sharingPlan (archaeology)Open dataResearch dataData managementBusinessProcess managementKnowledge managementComputer scienceEngineering managementData scienceWorld Wide WebEngineeringDatabaseMedicineData curation

Abstract

fetched live from OpenAlex

This is the Data Management Plan for the project "Exploring the opportunities and challenges of implementing open research strategies within development institutions" the proposal for which was published as https://doi.org/10.3897/rio.2.e8880. The research proposal calls for support for a pilot project to conduct open data pilot case studies with eight (8) IDRC grantees to develop and implement open data management and sharing plans. The results of the case studies will serve to refine guidelines for the implementation of development research funders’ open research data policies.

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)0.175
metaresearch head score (Gemma)0.230
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Open science
Consensus categoriesnone
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.994
Threshold uncertainty score0.927

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1750.230
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.007
Science and technology studies0.0080.003
Scholarly communication0.0100.007
Open science0.0060.013
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.1370.071

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 head0.727
GPT teacher head0.562
Teacher spread0.165 · 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
DomainReproducibility
GenreProtocol

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

Citations3
Published2017
Admission routes1
Has abstractyes

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