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Record W2982331061 · doi:10.3897/zookeys.884.38391

Dealing with a hairy beast–larval morphology and chaetotaxy of the Australian endemic diving beetle genus Spencerhydrus (Coleoptera, Dytiscidae, Cybistrini)

2019· article· en· W2982331061 on OpenAlexaff
Mariano C. Michat, Yves Alarie, C. H. S. Watts

Bibliographic record

VenueZooKeys · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicColeoptera Taxonomy and Distribution
Canadian institutionsLaurentian University
FundersAgencia Nacional de Promoción Científica y TecnológicaUniversidad de Buenos Aires
KeywordsChaetotaxyDytiscidaeInstarBiologyAppendageGenusZoologyLarvaMorphology (biology)TribeKey (lock)Taxonomy (biology)AnatomyBotanyEcologySeta

Abstract

fetched live from OpenAlex

In this contribution, the larval morphology of Spencerhydrus Sharp, 1882 was studied, an Australian endemic genus in the diving beetle tribe Cybistrini. All instars of the only two species included in the genus (S. latecinctus Sharp, 1882 and S. pulchellus Sharp, 1882) are described and illustrated with the exception of the third instar of S. latecinctus. Detailed morphometric and primary chaetotaxic analyses were performed to discover useful characters for generic diagnosis and species distinction. Spencerhydrus can be distinguished from other Cybistrini genera by the medial projection of frontoclypeus slightly indented apically, with lamellae clypeales directed forward in a characteristic V-shaped pattern, the median process of prementum strongly developed, the presence of a single ventral sclerite on prothorax, the presence of basoventral spinulae on claws, and the reduced sclerotization of the abdominal segment VII which covers only the anterior half. Larvae of the two species of Spencerhydrus can readily be distinguished by the shape of the median process of prementum, which is visibly broader in S. pulchellus than in S. latecinctus.

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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.015
GPT teacher head0.199
Teacher spread0.184 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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