MétaCan
Menu
Back to cohort
Record W4393004100 · doi:10.1007/s13225-023-00532-5

Current trends, limitations and future research in the fungi?

2024· article· en· W4393004100 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

VenueFungal Diversity · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
FundersInstitute of Botany, Chinese Academy of SciencesKunming Institute of Botany, Chinese Academy of SciencesFundação para a Ciência e a TecnologiaMinistério da Ciência, Tecnologia e Ensino SuperiorInstitute of Population and Public HealthNational Research Council of ThailandChinese Academy of SciencesCentro de Estudos Ambientais e Marinhos, Universidade de AveiroUniversidade de AveiroKing Saud UniversityMinisterstvo Školství, Mládeže a Tělovýchovy
KeywordsMycologyBiologyPhylogenomicsField (mathematics)EcologyData scienceEngineering ethicsComputer scienceEngineeringPhylogeneticsBotany

Abstract

fetched live from OpenAlex

Abstract The field of mycology has grown from an underappreciated subset of botany, to a valuable, modern scientific discipline. As this field of study has grown, there have been significant contributions to science, technology, and industry, highlighting the value of fungi in the modern era. This paper looks at the current research, along with the existing limitations, and suggests future areas where scientists can focus their efforts, in the field mycology. We show how fungi have become important emerging diseases in medical mycology. We discuss current trends and the potential of fungi in drug and novel compound discovery. We explore the current trends in phylogenomics, its potential, and outcomes and address the question of how phylogenomics can be applied in fungal ecology. In addition, the trends in functional genomics studies of fungi are discussed with their importance in unravelling the intricate mechanisms underlying fungal behaviour, interactions, and adaptations, paving the way for a comprehensive understanding of fungal biology. We look at the current research in building materials, how they can be used as carbon sinks, and how fungi can be used in biocircular economies. The numbers of fungi have always been of great interest and have often been written about and estimates have varied greatly. Thus, we discuss current trends and future research needs in order to obtain more reliable estimates. We address the aspects of machine learning (AI) and how it can be used in mycological research. Plant pathogens are affecting food production systems on a global scale, and as such, we look at the current trends and future research needed in this area, particularly in disease detection. We look at the latest data from High Throughput Sequencing studies and question if we are still gaining new knowledge at the same rate as before. A review of current trends in nanotechnology is provided and its future potential is addressed. The importance of Arbuscular Mycorrhizal Fungi is addressed and future trends are acknowledged. Fungal databases are becoming more and more important, and we therefore provide a review of the current major databases. Edible and medicinal fungi have a huge potential as food and medicines, especially in Asia and their prospects are discussed. Lifestyle changes in fungi (e.g., from endophytes, to pathogens, and/or saprobes) are also extremely important and a current research trend and are therefore addressed in this special issue of Fungal Diversity.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.683
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.109
GPT teacher head0.301
Teacher spread0.192 · 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