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Record W2089390415 · doi:10.1080/10888705.2014.856243

Variations of Some Physiological and Immunological Parameters in Siberian Sturgeon (<i>Acipenser baerii</i>, Brandt, 1869) Subjected to an Acute Stressor

2014· article· en· W2089390415 on OpenAlexaff
Khalil Eslamloo, Bahram Falahatkar

Bibliographic record

VenueJournal of Applied Animal Welfare Science · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSturgeonLysozymeStressorInternal medicineEndocrinologyFish <Actinopterygii>Animal scienceBiologyMedicineFisheryBiochemistry

Abstract

fetched live from OpenAlex

This study was carried out to investigate the effect of an acute stressor on the variation of some physiological and immunological parameters of Siberian sturgeon (Acipenser baerii) juveniles. Fish, reared in 3 tanks for 10 weeks, were used for this study. The acute stress of fish consisted of 2 min of air exposure stress. Plasma levels of cortisol, glucose, and lactate as well as lysozyme activity in plasma were measured before stress and 1 hr, 3 hr, 6 hr, 9 hr, 12 hr, and 24 hr after stress. The plasma cortisol significantly increased in the highest level 1 hr after stress, yet it gradually declined after 3 hr. The glucose significantly increased only 1 hr after stress. There was no significant difference between plasma lactate prestress and poststress. Moreover, lysozyme activity was enhanced by stress, thus reaching the highest level 9 hr after stress. The results of this study indicate that Siberian sturgeon not only have a rapid response to acute stress, but also a great capacity for recovery from stress, thus returning physiological parameters to prestress levels after 6 hr.

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 score0.002
Threshold uncertainty score0.004

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 studies0.0000.000
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 head0.009
GPT teacher head0.240
Teacher spread0.231 · 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

Citations22
Published2014
Admission routes1
Has abstractyes

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