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Record W4240868832 · doi:10.1139/z99-213

The ultrastructure of glands and the production and function of the secretion in the adhesive capture apparatus of<i>Stenus</i>species (Coleoptera: Staphylinidae)

2000· article· en· W4240868832 on OpenAlexvenueno aff
Gregor Kölsch

Bibliographic record

VenueCanadian Journal of Zoology · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsSecretionUltrastructureBiologyAdhesionAdhesiveCell biologyBiophysicsAnatomyBiochemistryMaterials scienceNanotechnologyComposite material

Abstract

fetched live from OpenAlex

The elongated labium of rove beetles of the genus Stenus forms an adhesive capture apparatus that enables them to catch fast-fleeing prey such as Collembola. The adhesion is mediated by a secretion produced in glands within the head capsule and secreted onto the paraglossae. Transmission electron microscopy has revealed that these "adhesive glands" are composed of discrete gland units, each consisting of three cells. Two cells are secretorily active, each producing a different secretion, one proteinaceous and the other lipoid. Consequently, a two-phase secretion can be found on the surface of the paraglossae. Adhesive glands and normal epidermal glands share several characteristics and are therefore considered to be homologous. Structural differences can be functionally interpreted. The long glandular ductules themselves serve as a reservoir for the secretion before it is expressed prior to the predatory strike. Van der Waals forces and both the surface tension and the viscosity of the adhesive secretion are discussed as possible mechanisms of adhesion. The adhesion resulting from the viscosity of the fluid is the strongest and exceeds the force theoretically required for catching collemboles.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 science0.0000.000
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 head0.005
GPT teacher head0.186
Teacher spread0.181 · 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

Citations23
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Zoology→Same topicInsect and Arachnid Ecology and Behavior→French-language works237,207→