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Record W2255781670 · doi:10.1071/mf15102

American eel (Anguilla rostrata) substrate selection for daytime refuge and winter thermal sanctuary

2016· article· en· W2255781670 on OpenAlexaffabout
J. P. N. Tomie, D. K. Cairns, Rod S. Hobbs, Mariève Desjardins, G. L. Fletcher, Simon C. Courtenay

Bibliographic record

VenueMarine and Freshwater Research · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMemorial University of NewfoundlandCape Breton UniversityHealth PEIUniversity of WaterlooFisheries and Oceans CanadaUniversity of New Brunswick
Fundersnot available
KeywordsAnguilla rostrataEstuaryBayFisheryCobbleOceanographySubstrate (aquarium)HabitatEnvironmental scienceAnguillidaeFish <Actinopterygii>BiologyEcologyGeology

Abstract

fetched live from OpenAlex

We addressed hypotheses that anguillid eels use mud as a substrate refuge only in the absence of substrate cavities, and that the winter distribution of eels in coastal bay and estuarine habitat is limited to waters warmer than the freezing point of fish tissue (~–0.7°C). In the seasonally ice-covered southern Gulf of St Lawrence, Canada, locations of summer fyke and winter spear fisheries indicate that American eels (Anguilla rostrata) are widely distributed in both summer and winter in shallow soft-bottomed bay and estuarine habitat. Captive eels in fresh water preferred mud substrates during summer, during pre-winter cooling and during post-winter warming periods, but in winter chose mud and cobble substrates at approximately equal frequencies. Plasma antifreeze was not detected in blood sampled from eels speared in mud under winter ice. Winter bottom water temperatures in an eel wintering site were below the approximate freezing point of fish tissue 29.9% of the time. Mud of eel wintering grounds is warmer than overlying water and appears to serve as a thermal sanctuary that allows eels to safely overwinter under ice-covered waters. American eels in the southern Gulf of St Lawrence spend ~67% of their annual cycle within the substrate.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 science0.0000.001
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 head0.025
GPT teacher head0.289
Teacher spread0.265 · 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 teacher head, not a consensus.

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

Citations21
Published2016
Admission routes2
Has abstractyes

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