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Record W2048294272 · doi:10.1094/pdis-11-12-1029-re

New Sources of Temperature-Sensitive Resistance to <i>Wheat streak mosaic virus</i> in Wheat

2013· article· en· W2048294272 on OpenAlexaff
Dallas L. Seifers, Steve Haber, T. J. Martin, Guorong Zhang

Bibliographic record

VenuePlant Disease · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyInoculationPotyviridaeAgronomyPlant virusVirusHorticulturePotyvirusVirologyVeterinary medicine

Abstract

fetched live from OpenAlex

Expressing temperature-sensitive resistance (TSR) protects wheat against yield losses from infection with Wheat streak mosaic virus (WSMV). In examining how 2,429 wheat accessions from the National Small Grains Collection responded to inoculation with the Sid81 isolate of WSMV, 20 candidate TSR sources were discovered. To differentiate their relative effectiveness, accession responses over 21 days to inoculation with GH95, Sid81, and PV57 virus isolates in regimes of 18 and 20°C were observed. At 18°C, all 20 candidate TSR sources were uniformly or nearly uniformly asymptomatic 21 days after inoculation with the PV57 isolate, resistance indistinguishable from resistant checks KS96HW10-3 and RonL. By contrast, the Sid81 isolate induced symptoms in low but significant proportions of plants of two candidates, and the GH95 isolate in high proportions for four candidates and low but significant proportions for two others. In the more stringent 20°C regime, the uniform or near-uniform induction of symptoms in response to inoculation with GH95 failed to differentiate among the 20 candidate TSR sources and two resistant checks, while PV57 and Sid81 identified several candidates that performed similarly to KS96HW10-3 and significantly better than RonL. By identifying new sources of resistance, this study contributes to the control of WSMV.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.847
Threshold uncertainty score0.805

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.224
Teacher spread0.209 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations28
Published2013
Admission routes1
Has abstractyes

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