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Record W4391360915 · doi:10.3390/horticulturae10020129

Pear Rootstock Effects on Seasonal Colonization Patterns of Pear Decline Phytoplasma

2024· article· en· W4391360915 on OpenAlexaff
Mina Kaviani, Paul H. Goodwin, David M. Hunter

Bibliographic record

VenueHorticulturae · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytoplasmas and Hemiptera pathogens
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPEARRootstockColonizationBiologyHorticultureBotanyEcology

Abstract

fetched live from OpenAlex

Pear decline (PD) phytoplasma populations were examined over one year in non-symptomatic pear trees with HW620 scions grafted onto three different rootstocks: OH×F87 (PD resistant), OH×F69 (PD susceptible), and Bartlett (PD susceptible). For all three rootstocks, populations were at a maximum during late summer for leaves and shoots, and reached their minimum in mid-winter for shoots and early spring for leaves. In contrast, roots exhibited maximum populations in mid-winter and minimum populations in mid-spring. For all tissue types, PD populations were consistently lowest in trees grafted onto OH×F87 rootstocks, intermediate in those on OH×F69, and highest on Bartlett rootstocks, demonstrating that the type of rootstock significantly impacts PD populations. While OH×F87 rootstocks had the lowest populations, they can still contain relatively high PD populations, particularly during periods with maximum populations. Future research could explore the development of even higher levels of PD resistance in pear rootstocks to reduce PD populations in both the rootstock and scion.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.220
Teacher spread0.210 · 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 designObservational
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

Citations4
Published2024
Admission routes1
Has abstractyes

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