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Record W7093335374 · doi:10.5281/zenodo.17415809

Report of the EUPHRESCO III stakeholders' consultations to develop a strategic research agenda

2025· article· en· W7093335374 on OpenAlexaffabout

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsCanadian Food Inspection Agency
FundersEuropean Commission
KeywordsWork (physics)Latin AmericansStrategic planningKey (lock)StakeholderAsia pacific

Abstract

fetched live from OpenAlex

Key factors for successful alignment of national research programmes include: the combination of (i) bottom-up alignment actions that involve research stakeholders and (ii) top-down alignment actions that involve decision makers (research funders and policymakers) and building mutual trust and consensus at all levels through regular consultations and dialogue1.In line with these recommendations, consultations of stakeholders that operate in plant health at national and regional level such as research funders, policy makers, research organizations, industry, farmers and foresters, were organized in the framework of the EUPHRESCO III project.The work was led by the EUPHRESCO III regional and discipline champions and the EUPHRESCO III project partners, the Advisory Board members and the network of Satellite Organizations were involved at different degrees, in identifying and selecting relevant stakeholders and collecting their needs and views via consultations.A mapping of stakeholders in the countries (Australia, Austria, Belgium, Canada, Denmark, Estonia, France, Germany, Great Britain, Greece, Italy, Latvia, the Netherlands, New Zealand, Norway, Poland, Portugal, Slovakia, Spain, Sweden, Switzerland, Türkiye, Uzbekistan, and the United States of America), regions (Africa, Australia, Latin America, Northern Europe, Southern Europe and Mediterranean, North America, Pacific islands, Central Asia and South-East Asia) and disciplines (biotech industry, diagnostic industry, seed industry and forest and tree health) covered by the project partners was undertaken. The stakeholders were interviewed via e-mail exchange, ad-hoc meetings, online surveys, conferences, etc.The regional champions consolidated the information collected at national level into a regional position, which was further prioritized with the help of decision makers in the countries/regions.The consultations have allowed to identify plant health needs that have been used to identify the research priorities for the annual calls for transnational collaboration and for the strategic research agenda.

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)0.042
metaresearch head score (Gemma)0.022
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: Empirical · Consensus signal: none
Teacher disagreement score0.042
Threshold uncertainty score0.221

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0060.001
Scholarly communication0.0080.003
Open science0.0020.009
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0130.003

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 head0.131
GPT teacher head0.281
Teacher spread0.150 · 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
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

Citations0
Published2025
Admission routes2
Has abstractyes

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