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Record W2889272449 · doi:10.5772/intechopen.77096

Systematic Identification of the Xylophilus Group in the Genus Bursaphelenchus

2018· book-chapter· en· W2889272449 on OpenAlexaboutno aff
Jianfeng Gu

Bibliographic record

VenueInTech eBooks · 2018
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicNematode management and characterization studies
Canadian institutionsnot available
FundersNingbo Municipal Science and Technology Innovative Research TeamGeneral Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China
KeywordsBursaphelenchus xylophilusXylophilusPinus thunbergiiSubspeciesWilt diseaseBiologyBotanyNematodeGenusPinus densifloraIdentification (biology)Invasive speciesPine woodGeographyEcology

Abstract

fetched live from OpenAlex

The pine wood nematode (PWN) Bursaphelenchus xylophilus (Steiner & Buhrer, 1934) Nickle, 1970 is the agent responsible for pine wilt disease (PWD). This nematode has been killing native pine trees (Pinus densiflora, P. thunbergii, P. luchuensis) in Japan since the early twentieth century. It is the number one forest pest in Japan and has been spread to China, Korea, Portugal, and Spain. The nematode is native to North America (Canada, USA, Mexico) and is thought to have been carried to Japan at the beginning of the twentieth century on timber exports. Up to now, the genus Bursaphelenchus Fuchs, 1937 comprises nearly 120 species (14 groups). Around 14 species very similar to B. xylophilus are put together and named the xylophilus group. This chapter presents the grouping history, subspecies or genetic types in species of the xylophilus group, and an identification key for 14 species of the xylophilus group, ITS-RFLP identification, and other molecular identification methods are also discussed.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.617
Threshold uncertainty score0.180

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 science0.0010.000
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 head0.024
GPT teacher head0.214
Teacher spread0.190 · 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 designBench or experimental
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
Published2018
Admission routes1
Has abstractyes

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