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Record W2970316970 · doi:10.1007/s11274-019-2709-7

Fungal biological resources to support international development: challenges and opportunities

2019· review· en· W2970316970 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWorld Journal of Microbiology and Biotechnology · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsnot available
FundersAustralian Centre for International Agricultural ResearchAgriculture and Agri-Food CanadaDepartment for International DevelopmentDirektion für Entwicklung und ZusammenarbeitMinistry of Agriculture of the People's Republic of ChinaEuropean Commission
KeywordsExploitLegislationBusinessDeveloping countrySustainable developmentEnvironmental planningPopulationGenetic resourcesEnvironmental resource managementEconomic growthPolitical scienceBiotechnologyBiologyEcologyGeographyEconomicsComputer science

Abstract

fetched live from OpenAlex

Exploitation of microbes, especially fungi, has the potential to help humankind meet the UN's sustainable development goals, help feed the worlds growing population and improve bioeconomies of poorer nations. The majority of the world's fungal genetic resources are held in collections in developed countries, primarily within the USA, Europe and Japan. Very little capacity exists in low to middle income countries, which are often rich in biodiversity but lack resources to be able to conserve and exploit their own microbial resources. In this paper we review the current challenges facing culture collections and the challenges of integrating new approaches, the worth of collaborative networks, and the importance of technology, taxonomy and data handling. We address the need to underpin research and development in developing countries through the need to build 'in country' infrastructure to address these challenges, whilst tackling the global challenges to meet the requirements of the research community through the impacts of legislation and the Nagoya protocol on access to biological resources.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.074
GPT teacher head0.282
Teacher spread0.208 · 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