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Record W6911863487 · doi:10.5281/zenodo.15021265

Euura tiliae Prous & Liston & Monckton & Kramp & Vårdal & Vikberg & Heibo & Mutanen 2025

2025· article· en· W6911863487 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Ecology and Invasive Species
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHolotypeType (biology)ClawGenetic dataHost (biology)

Abstract

fetched live from OpenAlex

331 Euura tiliae (Zinovjev, 1998) comb. nov. Nematus tiliae Zinovjev, 1998: 23–26. Diagnosis Could be confused with almost completely pale specimens of Euura miliaris or members of the E. bergmanni and E. oligospila groups. The rather short valvula 3 is most similar to E. jugicola, E. hypoxantha, and the E. papillosa group. The lancet is most similar to the E. papillosa group (overall shape, serrulae, and radix seems to be about as long as lamnium). Its darker pterostigma and not clearly bifid claws (somewhat similar to E. gregaria) distinguish E. tiliae from the species mentioned above. Without genetic data it is not clear to which Euura group E. tiliae could belong, but there seems to be little doubt that the species belongs to Euura rather than Nematus. Shinohara & Hara (2015) retained it in Nematus. We do not consider the small differences in claws to other Euura to be sufficient to exclude the species from this genus. Type material examined Holotype Nematus tiliae JAPAN – Hokkaido • ♀; Akaigawa, Meiji; 43.013° N, 140.898° E; 11 Sep. 1996; M. Ohara leg.; NSMT, NSMT-HYM62118. Host plants Tilia maximowicziana Shiras. (Zinovjev 1998). Genetics COI No data. Nuclear No data. Distribution and material examined East Palaearctic. Only one specimen studied, from Japan.

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: none
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.006

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 head0.016
GPT teacher head0.232
Teacher spread0.216 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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