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Record W2180345859 · doi:10.11646/zootaxa.4048.3.10

A new species of Pseudophanias Raffray from a cave in central Nepal (Coleoptera: Staphylinidae: Pselaphinae)

2015· letter· en· W2180345859 on OpenAlexaff
Zi‐Wei Yin, G. Coulon, Rostislav Bekchiev

Bibliographic record

VenueZootaxa · 2015
Typeletter
Languageen
FieldAgricultural and Biological Sciences
TopicColeoptera Taxonomy and Distribution
Canadian institutionsBGC Engineering (Canada)
Fundersnot available
KeywordsCaveBiologyKarstFaunaEcologyZoologyTribeSubfamilyPaleontology

Abstract

fetched live from OpenAlex

Cave-associated beetles of the subfamily Pselaphinae (Coleoptera: Staphylinidae) comprise some 170 species all over the world (Poggi et al. 1998 and subsequent papers), with Europe and North America having the highest species diversity (Besuchet 1985; Chandler 1992; Chandler & Reddell 2001; Hlaváč et al. 2006, 2008). The Asian fauna began to draw an increased attention after 2010 (Yin et al. 2011a, 2011b, 2015; Nomura 2012; Yin & Li 2015), with the number of the species growing from 10 to 25. Most of these species were found in southern to southwestern China and Japan, where many caves are scattered in the karst areas. However no species has been so far known from the Himalayan region. Most species of cavernicolous pselaphines belong to the tribes Batrisini, Amauropini, and Bythinini, while members are relatively rare in other tribes. Currently, the pselaphite tribe Tmesiphorini has no true troglobitic/cavernicolous species; all of the few existing records indicated that occurrence of some species of the genera Dacnotillus Raffray, Tmesiphorus LeConte, and Tmesiphorites Jeannel at the entrance or inside of caves or sinkholes are probably accidental, because there are no obvious morphological adaptions for cavernicolous life, and some species (e.g., Tmesiphorus costalis LeConte) are widely distributed, being found also in leaf litters, under bark, and with ants (Raffray et al. 1892; Chandler 1992; Jeannel 1953).

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.215
Teacher spread0.188 · 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.

Study designNot applicable
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

Citations8
Published2015
Admission routes1
Has abstractyes

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