MétaCan
Menu
Back to cohort
Record W4411450856 · doi:10.1002/2688-8319.70031

Grey matters: Ensuring management information is a part of the permanent evidence base by creating open grey literature principles

2025· article· en· W4411450856 on OpenAlexaff
Marc W. Cadotte, Menilek Beyene, Mark Bowell, Sarah E. Dalrymple, Michele de Sá Dechoum, Philip Dooner, Errol Douwes, Rosemary S. Hails, Holly P. Jones, Carolyn M. Kurle, N. J. Pates, Minhyuk Seo, William J. Sutherland

Bibliographic record

VenueEcological Solutions and Evidence · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicGrey System Theory Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGrey literatureBase (topology)Computer scienceKnowledge managementData sciencePolitical scienceMEDLINEMathematicsLaw

Abstract

fetched live from OpenAlex

Sharing project outcomes for practitioners comes with a number of hurdles and barriers, but the benefits far outway these. We argue for a shift to open sharing of grey literature.

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)0.411
metaresearch head score (Gemma)0.524
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Open science
Consensus categoriesMetaresearch
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.727

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4110.524
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0140.011
Science and technology studies0.0120.060
Scholarly communication0.0400.059
Open science0.0110.050
Research integrity0.0250.019
Insufficient payload (model declined to judge)0.0140.006

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 head0.146
GPT teacher head0.368
Teacher spread0.222 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainReproducibility
GenreEmpirical

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

Citations4
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueEcological Solutions and EvidenceSame topicGrey System Theory ApplicationsFrench-language works237,207