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Variability within Clones of Potato cv. Russet Burbank to Infection and Severity of Common Scab Disease of Potato

2001· article· en· W2162093174 on OpenAlexaboutno aff
CR Wilson

Bibliographic record

VenueJournal of Phytopathology · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsSolanum tuberosumBiologyCultivarHorticultureSolanaceaeIncidence (geometry)clone (Java method)Cluster (spacecraft)InoculationVeterinary medicinePlant disease resistanceMedicineGenetics

Abstract

fetched live from OpenAlex

Significant variability in the level of resistance to common scab disease (to both disease incidence – tuber surface area affected, and severity – lesion depth) within potato (Solanum tuberosum) cv. Russet Burbank clonal lines and other selected processing cultivars was shown. Across two trials, cvs. Russet Nugget and Shepody and Russet Burbank clone British Columbia were consistently grouped within the cluster of least disease incidence whereas cv. Russet Norkotah and Vancouver unit four were grouped within the cluster showing greatest disease incidence. Russet Nugget and British Columbia were also consistently grouped within the cluster showing least disease severity, whereas Shepody and Russet Burbank clone Starks were grouped within the cluster with greatest severity scores. For some clones, consistency of rating across trials was not always apparent. Of note for the Tasmanian industry, there were differences within the five commercial Vancouver clonal units used interchangeably, with unit 4 showing significantly greater disease severity and incidence than some of the other units. However the extent of increased disease never exceeded 1.75 times the best of the other Vancouver units and the relevance of these results to the relative field performance of unit 4 remains to be tested.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.011
GPT teacher head0.239
Teacher spread0.227 · 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

Citations17
Published2001
Admission routes1
Has abstractyes

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