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Record W2166946326 · doi:10.1242/jeb.125047

Gas exchange and dive characteristics of the free-swimming backswimmer <i>Anisops deanei</i>

2015· article· en· W2166946326 on OpenAlexfundno aff
Karl K. Jones, Edward P. Snelling, Amy P. Watson, Roger S. Seymour

Bibliographic record

VenueJournal of Experimental Biology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsnot available
FundersUniversity of British ColumbiaUniversity of Adelaide
KeywordsBuoyancyNeutral buoyancyVolume (thermodynamics)Gas bubbleEnvironmental scienceAir bubbleBubbleChemistryMechanicsBiologyFisheryThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Many aquatic insects utilise air bubbles on the surface of their bodies to supply O2 while they dive. The bubbles can simply store O2, as in the case of an 'air store', or they can act as a physical 'gas gill', extracting O2 from the water. Backswimmers of the genus Anisops augment their air store with O2 from haemoglobin cells located in the abdomen. The O2 release from the haemoglobin helps stabilise bubble volume, enabling backswimmers to remain near neutrally buoyant for a period of the dive. It is generally assumed that the backswimmer air store does not act as a gas gill and that gas exchange with the water is negligible. This study combines measurements of dive characteristics under different exotic gases (N2, He, SF6, CO) with mathematical modelling, to show that the air store of the backswimmer Anisops deanei does exchange gases with the water. Our results indicate that approximately 20% of O2 consumed during a dive is obtained directly from the water. Oxygen from the water complements that released from the haemoglobin, extending the period of near-neutral buoyancy and increasing dive duration.

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 score0.004
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.256
Teacher spread0.226 · 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

Citations10
Published2015
Admission routes1
Has abstractyes

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