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Record W1980129068 · doi:10.1094/phyto-98-10-1118

Assessment of Common Scab-Inducing Pathogen Effects on Potato Underground Organs Via Computed Tomography Scanning

2008· article· en· W1980129068 on OpenAlexaff
Liwen Han, Pierre Dutilleul, Shiv O. Prasher, Carole Beaulieu, Donald L. Smith

Bibliographic record

VenuePhytopathology · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsMcGill University
Fundersnot available
KeywordsCommon scabBiologySowingSolanum tuberosumHorticultureComputed tomographyVeterinary medicineStreptomycesRadiologyMedicineBacteria

Abstract

fetched live from OpenAlex

Common scab caused by Streptomyces scabies is a major bacterial disease of potato (Solanum tuberosum). Its best known symptom is superficial lesions on the surface of progeny potato tubers, observed at harvesting. In this study, effects of S. scabies on space occupancy by underground organs and on structural complexity of root systems are investigated during growth via computed tomography (CT) scanning. Two groups of potato plants were grown in a greenhouse in middle-sized plastic pots. Using a high-resolution X-ray CT scanner formerly used for medical applications, their underground organs and surrounding medium (sieved and autoclaved homogeneous sand) were submitted to CT scanning 4, 6, and 8 weeks after planting. For one group, sand was inoculated with the common scab-inducing pathogen (S. scabies EF-35) at potting. Space occupancy by underground organs was estimated via curve fitting applied to histograms of CT scan data, while three-dimensional skeletal images were used for fractal analysis. Root systems of diseased plants were found to be less complex than those of healthy plants 4 weeks after planting, and the relative growth rates derived from space occupancy measures were of different sign between the two groups from week 4 to week 8.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.701
Threshold uncertainty score0.329

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 head0.238
Teacher spread0.223 · 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 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

Citations35
Published2008
Admission routes1
Has abstractyes

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