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Record W2170586625 · doi:10.1139/b05-125

The effects of the smut fungus <i>Microbotryum bistortarum</i> on survival and growth of <i>Polygonum viviparum</i> in Svalbard, Norway

2005· article· en· W2170586625 on OpenAlexvenueno aff
Motoaki Tojo, Satomi Nishitani

Bibliographic record

VenueCanadian Journal of Botany · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceNational Institute of Advanced Industrial Science and Technology
KeywordsSmutBiologyFungusBotanyGermination

Abstract

fetched live from OpenAlex

The effect of the smut fungus Microbotryum bistortarum (de Candolle) K. Vánky on Polygonum viviparum L. was investigated in the High Arctic region, Svalbard, Norway, from 2000 to 2004. Ninety-two plants in a field plot were monitored for disease occurrence, plant survival, and plant growth. The disease, initially identified in 20 plants, only spread to one additional plant in 4 years. Once infected, the plants remained infected. Although a few of the 71 uninfected plants disappeared or died without any apparent signs of disease, the majority remained healthy without smut throughout the study. The percent survival among smut-infected plants was significantly lower than that of healthy plants in 2004 (P < 0.001). The number of bulbils, the number of flowers, and the size of the largest leaves of smut-infected plants were significantly lower than those of healthy plants. These results suggest infection by M. bistortarum can negatively impact populations of P. viviparum in the High Arctic region by lowering plant growth and longevity. Teliospore surface characteristics and germination patterns of the High Arctic specimens of M. bistortarum were also documented.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

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 head0.003
GPT teacher head0.181
Teacher spread0.177 · 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

Citations8
Published2005
Admission routes1
Has abstractyes

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