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Record W4399692830 · doi:10.1163/15685411-bja10335

Unveiling novel and known Cryptaphelenchus species from China and USA

2024· article· en· W4399692830 on OpenAlexaff
Jianfeng Gu, Pablo Castillo, Xinxin Ma, Munawar Maria

Bibliographic record

VenueNematology · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNematode management and characterization studies
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsBiologyTaxonomy (biology)Bark (sound)Phylogenetic treeNematologyBotanyZoologyBark beetleEcologyNematode

Abstract

fetched live from OpenAlex

Summary Cryptaphelenchus species are wood- or bark-inhabiting nematodes, generally mycetophagous and reported to have endophoretic associations with insects. In the present study, we describe two new and one known Cryptaphelenchus species detected in imported and domestic wood samples. Cryptaphelenchus americanum n. sp. and C. minutus were detected in the log samples of Pinus taeda imported from the USA, whereas C. orientalis n. sp. was isolated from the bark of dying Pinus sylvestris trees in Inner Mongolia, China. Both new species displayed characteristic features, including a relatively short body length, four lateral lines, a short post-vulval uterine sac in females, and a distinct cloacal apophysis in male tails. Newly recovered and known species were characterised molecularly, and phylogenetic trees were constructed to study their relationship with related Cryptaphelenchus species. Notably, the genetic divergence observed among Cryptaphelenchus species was found to be more significant compared to morphometrical differences, highlighting the importance of molecular data in taxonomy. The identification of new and known species expands our understanding of the genus and suggests that Cryptaphelenchus species may be under studied, underscoring the necessity for continued exploration.

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 score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
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 head0.019
GPT teacher head0.214
Teacher spread0.195 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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