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Record W2123186487 · doi:10.5539/jps.v2n1p36

Spatial Distribution Pattern of Pine Trees Killed by Pine Wilt Disease in a Sparsely Growing, Young Pine Stand

2012· article· en· W2123186487 on OpenAlexvenueno aff
Koichi Soné, Keisuke Ohkubo, Toshiyuki Matsuo, Kunihiko Hata

Bibliographic record

VenueJournal of Plant Studies · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
Fundersnot available
KeywordsWilt diseaseSpatial distributionBiologyWoody plantPine woodPine forestBotanyEcologyGeography

Abstract

fetched live from OpenAlex

We studied the spatial distribution pattern of surviving Japanese black pine trees and those killed by pine wilt disease in 2008 and 2009 in a sparsely growing, young stand on a lava field in Sakurajima, Kagoshima Prefecture, southern Japan. Pine trees were distributed aggregately and formed loose colonies occupying an area of 16 - 25 m2. Pine trees killed by pine wilt disease in 2008 and 2009 also occurred in loose colonies of 16-25 m2 in area. However, the spatial distribution pattern of pine trees killed in 2009 was exclusive to that in 2008, and killed trees in 2009 occurred in colonies of pine trees where no killed pine trees occurred in 2008. Asymptomatic carrier trees might not have any significant impacts on the spatial pattern of killed trees. This spreading of pine wilt disease might have been caused by the active flight of the Japanese pine sawyer beetles and rapid invasion of the pinewood nematodes into sound trees just after the beetles emerged.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.235
Teacher spread0.217 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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