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Record W4285594834 · doi:10.3390/insects13070632

The Effect of Species Soybean Vein Necrosis Orthotospovirus (SVNV) on Life Table Parameters of Its Vector, Soybean Thrips (Neohydatothrips variabilis Thysanoptera: Thripidae)

2022· article· en· W4285594834 on OpenAlexfundaboutno aff
Asifa Hameed, Cristina Rosa, Edwin G. Rajotte

Bibliographic record

VenueInsects · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsnot available
FundersHatchPennsylvania Soybean Board
KeywordsBiologyThripidaeThripsPopulationPopulation dynamicsVector (molecular biology)InstarReproductionVeterinary medicineBotanyToxicologyHorticultureLarvaFecundityEcologyDemography

Abstract

fetched live from OpenAlex

(Beach, 1896), and to a lesser extent by five other thrips species. There is increasing incidence of soybean vein necrosis (SVN) disease in all soybean growing states in the United States, Canada, Egypt and Pakistan, necessitating a study of the system's ecology and management. We addressed the effect of SVNV on the life table parameters of the vector. We used an 'age-stage two-sex' life table approach, which provided detailed life stage durations of each larval instar and adults (both sexes). Our results showed that the intrinsic rate of increase (r), finite rate of increase (λ) and mortality index (qx) were higher in the infected population, while the net reproduction rate (Ro), cumulative probability of survival (lx) and gross reproduction rate (GRR) were lower in the uninfected population. Overall, in both infected and uninfected populations, the number of eggs producing haploid males via arrhenotoky ranged from 9-12 per female. Male to female ratio was female biased in the infected population. Overall, our study provided evidence that virus infection, by decreasing the population doubling time, could enhance the virus and vector populations in soybeans.

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)0.002
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.026
GPT teacher head0.232
Teacher spread0.206 · 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

Citations8
Published2022
Admission routes2
Has abstractyes

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