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Record W3202853796 · doi:10.3390/f12101323

Dothistroma septosporum Not Detected in Pinus sylvestris Seed Trees from Investigated Stands in Southern Poland

2021· article· en· W3202853796 on OpenAlexaff
Pola Wartalska, Tomasz Oszako, С. Бакиер, Lassaâd Belbahri, Tadeusz Malewski, Tom Hsiang, E. Popowska‐Nowak, Justyna A. Nowakowska

Bibliographic record

VenueForests · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPinus radiataPinus pinasterBotanyPhytosanitary certificationBiologyPinus <genus>RadiataWoody plantMycosphaerellaHorticulture

Abstract

fetched live from OpenAlex

In recent years, the decline of pine stands in Europe, including Poland, has been caused by the emerging needle pathogen Dothistroma septosporum. Although this fungus appears to preferentially infect Pinus pini, P. pinaster or P. radiata in Southern Europe, it has been reported in stands of P. nigra, P. mugo and P. sylvestris from Southern Poland. Our preliminary tests of symptomatic needles of diseased pines, including black pine (P. nigra), showed the presence of both D. septosporum and D. pini—the latter as the first report in Poland. No other endophytic pathogen, i.e., Lecanosticta acicola or Cenangium ferruginosum, were found. More extensive molecular surveying based on β-tub2 amplification of DNA in needle samples from 72 seed trees of P. sylvestris in nine different Forest Districts of Southern Poland did not find the presence of D. septosporum. Our study revealed that the seed trees from which we collected propagation material were free from the pathogen, and its endophytic behavior was not confirmed in our testing. Consequently, these investigated trees of P. sylvestris should be suitable for seed collection and propagation, following the requirements of “good” phytosanitary quality as “pathogen-free” pine seeds used for reforestation.

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 score0.432
Threshold uncertainty score0.976

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 head0.009
GPT teacher head0.211
Teacher spread0.202 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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