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Record W1947133514 · doi:10.1139/cjfas-2013-0463

Physiological differences between lean and siscowet lake trout morphotypes: Are these metabolotypes?

2013· article· en· W1947133514 on OpenAlexvenueno aff
Frederick W. Goetz, Andrew Jasonowicz, Ronald B. Johnson, Peggy R. Biga, Gregory J. Fischer, Shawn P. Sitar

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsnot available
FundersU.S. Fish and Wildlife ServiceUniversity of Wisconsin-MilwaukeeGreat Lakes Fishery Commission
KeywordsTroutSalvelinusBiologyGlycogenReproductionZoologySalmonidaeAnimal scienceEcologyFisheryEndocrinologyFish <Actinopterygii>Rainbow trout

Abstract

fetched live from OpenAlex

Results of a past study on lean and siscowet lake trout (Salvelinus namaycush) reared under identical conditions from conception indicated that differences in growth and morphometry between these morphotypes have a genetic basis. Using these cultured lake trout, we found that siscowet lake trout had higher lipid levels and lower glycogen levels as compared with lean lake trout in skeletal muscle and liver. Lean lake trout also had higher circulating levels of lipids and glucose compared with siscowet lake trout. Analysis of F1progeny from crosses of the cultured morphotypes showed that progeny of crosses between siscowet females and siscowet males had higher lipid levels than all other crosses. The combined results indicate that the lake trout morphotypes differ substantially in the storage of energy, which may be related to their specific life histories. Siscowets store energy preferentially as lipid and appear to be more efficient in moving lipid from the blood into the muscle and liver. The lipid in siscowets may be adaptive for regulating buoyancy as well as an essential energy reserve for reproduction.

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 score0.007
Threshold uncertainty score0.013

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 head0.040
GPT teacher head0.209
Teacher spread0.169 · 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

Citations34
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicAquaculture Nutrition and GrowthFrench-language works237,207