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Record W2125969839 · doi:10.1139/x09-097

The effects of Phytophthora ramorum infection on hydraulic conductivity and tylosis formation in tanoak sapwood

2009· article· en· W2125969839 on OpenAlexvenueno aff
Bradley R. Collins, Jennifer L. Parke, B. Lachenbruch, Everett M. Hansen

Bibliographic record

VenueCanadian Journal of Forest Research · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsnot available
FundersU.S. Forest ServiceU.S. Department of Agriculture
KeywordsBiologyPhytophthora ramorumXylemOomyceteInoculationBotanyPhytophthoraHorticultureMicrobiology

Abstract

fetched live from OpenAlex

Tanoak ( Lithocarpus densiflorus (Hook. and Arn.) Rehder) is highly susceptible to sudden oak death, a disease caused by the oomycete Phytophthora ramorum Werres, De Cock & Man in’t Veld. Symptoms include a dying crown, bleeding cankers, and, eventually, death of infected trees. The cause of mortality is not well understood, but recent research indicates that water transport is reduced in infected trees. One possible mechanism causing the reduction in hydraulic conductivity is the presence of tyloses in xylem vessels. The development of tyloses was studied in relation to hydraulic conductivity in P. ramorum-infected sapwood. Inoculated logs showed a greater abundance of tyloses than noninoculated logs after 4 weeks. Inoculated trees with xylem infections had significantly more tyloses than noninoculated trees. In addition, the increase in number of tyloses was associated with a decrease in specific conductivity, suggesting that tyloses induced by infection with P. ramorum may interfere with stem sap flow. Over time, tylosis development increased in tissues farther from the inoculation site, in advance of the vertical spread of infection. The results suggest that infected sapwood contains numerous tyloses, which could significantly impede stem water transport.

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)0.001
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 score0.883
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.028
GPT teacher head0.265
Teacher spread0.237 · 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

Citations44
Published2009
Admission routes1
Has abstractyes

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