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Record W7108753424 · doi:10.5281/zenodo.17816589

E-RIHS CoS Guidelines for Users

2025· article· W7108753424 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Language
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsRoyal Inland Hospital
Fundersnot available
KeywordsService (business)Sample (material)Point (geometry)Public accessProcess (computing)Data access

Abstract

fetched live from OpenAlex

The E-RIHS Catalogue of Services (CoS) is the single-entry point for accessing the four E-RIHS service platforms:• MOLAB for in situ, non-invasive analysis using portable equipment• FIXLAB for access to large-scale, stationary analytical facilities• ARCHLAB for access to curated scientific archives and sample collections• DIGILAB for access to digital tools.Access is granted through competitive peer-reviewed calls for access. These guidelines explain how to create a user account, submit an access application, and follow the process from selection to post-access reporting.

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)0.028
metaresearch head score (Gemma)0.102
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.695

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.102
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.007
Science and technology studies0.0030.002
Scholarly communication0.0120.011
Open science0.0050.009
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.5130.619

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 head0.192
GPT teacher head0.378
Teacher spread0.187 · 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
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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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