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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

Members of the Fungal kingdom are ubiquitous in nature. Over the course of evolution, fungi have adapted to occupy specifi c niches, from symbiotically inhabiting the fl ora of the intestinal tract of mammals to saprophytic growth on leaf litter resting on the forest fl oor. Modern agricultural cropping systems have offered fungal plant pathogens vast amounts of substrate for colonization, resulting in disease development. Although the long-term goal for plant pathologists and geneticists is to breed for genetic resistance to combat fungal pathogens, a glimpse at the history of plant breeding has shown that breeders play an ongoing chess game against plant pathogens without a clear winner so far.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.879
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.000
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 head0.025
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 teacher head, not a consensus.

Study designBench or experimental
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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