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Record W7116425616 · doi:10.5281/zenodo.17986457

D8.1 - Implementation report on support for "early adopters" and training interventions

2025· article· en· W7116425616 on OpenAlexaff
Maaike Verburg, Joy Davidson, Laurence Horton, Tuomas J. Alaterä, Henna Kaartinen, Willem Elbers, Nadine Fischer, Vasso Kalaitzi, Geert van Geest, Gilles Mathieu, Helena Lozano, Deborah Thorpe, Anja Radonjic

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Languageen
FieldComputer Science
TopicInformation Architecture and Usability
Canadian institutionsCanarie
FundersEuropean Commission
KeywordsDeliverableBridging (networking)Psychological interventionTraining (meteorology)Best practiceCommunity of practice

Abstract

fetched live from OpenAlex

The FIDELIS Repository Training and Support Pillar is responsible for developing and delivering a comprehensive programme of support types which address the needs of the repository community regarding trustworthiness skills. This report details the activities of the first year of the project and how these will inform the upcoming activities in the next years. The training and support programme consists of three different support types: Support for the Adoption of Solutions: A mix of financial support and expert guidance will support repositories to implement and adopt good practices, tools, services, and other solutions to increase their trustworthiness. Peer-to-peer Mentoring Programme: A programme to connect mentors and mentees on specific TTRAM topics, bridging gaps in the current landscape and building the peer-to-peer support attitude that the FIDELIS Network will thrive on. Open Training Activities: Different events which are open for all to join, designed to share and teach about different topics and solutions relevant to the repository community. They include webinars, which focus more on information sharing and topical discussions, and training interventions, which include some interactive element for the audience. A comprehensive training strategy has been developed based on the insights gathered from the landscape study, pilot testing, and the delivery of the first training activities. Through this, the different types of support were defined and refined, and will be delivered more widely in the first open calls next year. This deliverable report details the different choices made and topics considered around developing this strategy, as well as the outcomes of the pilot support round and further community engagement. This transparent presentation of rationale, considerations, and decisions made shows the community what can be expected from the FIDELIS Repository Training and Support Pillar and how repositories can participate in the different programmes and activities.

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)0.062
metaresearch head score (Gemma)0.090
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.115
Threshold uncertainty score0.385

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0620.090
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0040.001
Scholarly communication0.0050.003
Open science0.0050.010
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.1150.027

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 head0.053
GPT teacher head0.320
Teacher spread0.267 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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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