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Record W2460250987 · doi:10.1242/jeb.141598

It's all in the gills: Evaluation of O2 uptake in Pacific hagfish refutes a major respiratory role for the skin

2016· article· en· W2460250987 on OpenAlexafffund
Alexander M. Clifford, Alex M. Zimmer, Chris M. Wood, Greg G. Goss

Bibliographic record

VenueJournal of Experimental Biology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of British ColumbiaBamfield Marine Sciences CentreUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHagfishExcretionGillBiologyAmmoniaRespiratory systemAnatomyInternal medicineEndocrinologyFisheryVertebrateBiochemistryMedicineFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Hagfish skin has been reported as an important site for ammonia excretion and as the major site of systemic oxygen acquisition. However, debate remains whether cutaneous O2 uptake is the dominant route of uptake; all evidence supporting this hypothesis has been derived using indirect measurements. Here we use separating chambers and direct measurements of oxygen consumption and ammonia excretion to quantify cutaneous and branchial exchanges in Pacific hagfish (Eptatretus stoutii) at rest and following exhaustive exercise. Hagfish primarily relied on the gills for both O2 uptake (81.0%) and ammonia excretion (70.7%). Following exercise, both O2 uptake and ammonia excretion increased, but only across the gill; cutaneous exchange was not increased. When branchial O2 availability was reduced by exposure to anteriorly-localized hypoxia (∼4.6 kPa O2), cutaneous O2 consumption was only slightly elevated on an absolute basis. These results refute a major role for cutaneous O2 acquisition in the Pacific hagfish.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

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 studies0.0000.001
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 head0.069
GPT teacher head0.335
Teacher spread0.266 · 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

Citations20
Published2016
Admission routes2
Has abstractyes

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