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Record W3046868817 · doi:10.1071/fp19327

Identification and functional characterisation of late blight resistance polymorphic genes in Russet Burbank potato cultivar

2020· article· en· W3046868817 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFunctional Plant Biology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsMcGill UniversitySte. Anne's Hospital
Fundersnot available
KeywordsIndelBiologyPhytophthora infestansGeneGeneticsSingle-nucleotide polymorphismBlightPlant disease resistancePhenylpropanoidGenomeGenotypeBotanyBiosynthesis

Abstract

fetched live from OpenAlex

In plants, the biosynthesis of the phenylpropanoid, flavonoid and fatty acid pathway monomers, polymers and conjugated metabolites play a vital role in disease resistance. These are generally deposited to reinforce cell walls to contain the pathogen to the site of infection. Identification of sequence variants in genes that biosynthesise these resistance metabolites can explain the mechanisms of disease resistance. The resistant and susceptible genotypes inoculated with Phytophthora infestans were RNA sequenced to identify the single nucleotide polymorphisms (SNPs) and insertion/deletion (InDel) variations. The SNPs/InDels were annotated and classified into different categories based on their effect on gene functions. In the selected 25 biosynthetic genes overlapping 39 transcripts, a total of 52 SNPs/InDels were identified in the protein-coding (CDS) regions. These were categorised as deleterious based on prediction of their effects on protein structure and function. The SNPs/InDels data obtained in this study can be used in genome editing to enhance late blight resistance in Russet Burbank and other potato cultivars.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.947
Threshold uncertainty score0.203

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 head0.027
GPT teacher head0.191
Teacher spread0.164 · 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