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Record W2031361267 · doi:10.1139/z04-099

Thyroid function in growth-hormone-transgenic coho salmon (<i>Oncorhynchus kisutch</i>)

2004· article· en· W2031361267 on OpenAlexvenueno aff
J.G. Eales, Robert H. Devlin, David A. Higgs, J. M. McLeese, Janice Oakes, James Plohman

Bibliographic record

VenueCanadian Journal of Zoology · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Genetics and Reproduction
Canadian institutionsnot available
Fundersnot available
KeywordsInternal medicineEndocrinologyOncorhynchusTriiodothyronineBiologyHormoneMetabolismFish <Actinopterygii>Fishery

Abstract

fetched live from OpenAlex

We measured growth rate, plasma thyroxine (T 4 ) and 3,5,3'-triiodothyronine (T 3 ) concentrations, and liver and whole-brain T 4 and T 3 deiodination activities in yearling non-transgenic coho salmon, Oncorhynchus kisutch (Walbaum, 1792), fed a satiation ration (NT S ) and in growth-hormone (GH)-transgenic salmon fed for 63 d with either a satiation ration (T S ) or pair-fed the satiation ration consumed by NT S fish (T NT ). Daily feed intake and specific growth rate for T S fish were significantly enhanced and approximately double those for T NT and NT S fish. There were no differences among groups in plasma T 4 concentration or liver T 4 outer-ring deiodination activity, but for both T S and T NT fish, plasma T 3 concentrations were higher and liver T 4 and T 3 inner-ring deiodination activities were lower than for NT S fish. Whole-brain deiodination activities did not differ between T S and NT S fish. We conclude that the elevated plasma T 3 concentrations of GH-transgenic salmon neither are driven by elevated plasma T 4 concentrations nor are they the result of increased hepatic conversion of T 4 to T 3 by outer-ring deiodination. Instead they can be explained, at least in part, by reduced hepatic degradation of T 3 to 3,3'-diiodothyronine by inner-ring deiodination. These changes in T 4 and T 3 metabolism are tightly linked to the GH-transgenic state and not to food intake or growth rate.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.814
Threshold uncertainty score0.981

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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.

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

Citations18
Published2004
Admission routes1
Has abstractyes

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