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Record W3095631952 · doi:10.1139/cjfas-2020-0177

A less invasive system for the direct measurement of ventilation in fish

2020· article· en· W3095631952 on OpenAlexaffvenue
Junho Eom, Chris M. Wood

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRainbow troutVentilation (architecture)TroutFish <Actinopterygii>Carassius auratusBiologyEnvironmental scienceFisheryEngineering

Abstract

fetched live from OpenAlex

Most previous systems for quantifying ventilatory flow in fish involve prior anesthesia and difficult surgery to sew or glue membranes to the animal, which are undoubtedly stressful. By modification of the original “van Dam box” design and incorporation of an electromagnetic blood flow probe, we have developed a less invasive system that avoids these problems and provides breath-to-breath measurements of ventilatory flow in real time. The fish can be quickly moved in and out of the apparatus, facilitating repeated measurements on the same animal after different treatments. We have used the system to document the hyperventilatory and hypoventilatory responses to environmental hypoxia and hyperoxia, respectively, in both ∼400-g trout (Oncorhynchus mykiss) and 10-g goldfish (Carassius auratus); the method is easily adaptable to fish of other sizes. Separate experiments on trout have demonstrated that responses to these treatments in buccal pressure amplitude, breathing frequency, and ventilation index are not altered by the attachments used in the apparatus. This less invasive methodology may prove more acceptable to animal ethics committees.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.070
GPT teacher head0.210
Teacher spread0.141 · 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 designBench or experimental
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

Citations4
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicPhysiological and biochemical adaptations→French-language works237,207→