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Record W1494227505 · doi:10.1007/978-1-61779-501-5

Plant Fungal Pathogens

2011· book· en· W1494227505 on OpenAlexfundno aff
Melvin D. Bolton, Bart P. H. J. Thomma

Bibliographic record

VenueMethods in molecular biology · 2011
Typebook
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsnot available
FundersWageningen University and ResearchAgriculture and Agri-Food CanadaUniversité de MontpellierAgricultural Research ServiceMax-Planck-Institut für Terrestrische MikrobiologieDanmarks Tekniske UniversitetChinese Academy of SciencesUniversiteit van AmsterdamMurdoch UniversityDirectorate for Biological SciencesRijksuniversiteit GroningenAalborg UniversitetCurtin University of TechnologyBroad InstitutePennsylvania State UniversityWest Chester UniversityAustralian National UniversityNorth Dakota State UniversityUniversiteit LeidenU.S. Department of AgricultureMassachusetts Institute of TechnologyHelsingin YliopistoNational Key Laboratory of Plant Molecular GeneticsUrmia UniversityVirginia Polytechnic Institute and State UniversityIowa State University
KeywordsFlora (microbiology)BiologyEcological nicheLitterMicrobiologyNicheBotanyEcologyBacteriaGeneticsHabitat

Abstract

fetched live from OpenAlex

Over the course of evolution, fungi have adapted to occupy specific niches, from symbiotically inhabiting the flora of the intestinal tract of mammals to saprophytic growth on leaf litter resting on the forest floor. In Plant Fungal Pathogens: Methods and Protocols, expert researchers in the field detail many of the methods which are now commonly used to study fungal plant pathogens. These include methods and techniques for model systems such as Arabidopsis thaliana as well as crop plants, aspects of fungal biology, genome annotation, next-generation sequencing, and fungal transformation and molecular tools for disease and/or pathogen quantification that are critical for revealing the role for a fungal gene of interest in disease development. Chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.040
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0400.049

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 head0.025
GPT teacher head0.319
Teacher spread0.295 · 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

Citations52
Published2011
Admission routes1
Has abstractyes

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