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Record W1717202010 · doi:10.1139/z2012-097

Muscle cellularity, enzyme activities, and nucleic acid content in meagre (<i>Argyrosomus regius</i>)

2012· article· en· W1717202010 on OpenAlexvenueno aff
Ioannis Mittakos, M. D. Ayala, Octavio López‐Albors, Kriton Grigorakis, Dimitrios Lenas, Fotini Kakali, Cosmas Nathanailides

Bibliographic record

VenueCanadian Journal of Zoology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyMuscle hypertrophyCytochrome c oxidaseAnimal scienceGrowth rateLactate dehydrogenaseMuscle tissueEnzymeEndocrinologyInternal medicineAnatomyBiochemistry

Abstract

fetched live from OpenAlex

Anatomical and biochemical indices of axial muscle growth were monitored in farmed meagre ( Argyrosomus regius (Asso, 1801)), a species with larger ultimate size. Within the first 19 months of a production cycle, body mass exceeded 1300 g. The specific daily growth rate ranged from a winter low of 0.2% to a summer high of 1.3%. Axial muscle RNA:DNA ratio decreased and cytochrome c oxidase levels increased from spring to winter, indicating a metabolic reorganisation of this tissue in response to winter temperature lows. Body mass correlated positively with increased lactate dehydrogenase activity and myofibre size (hypertrophy). The DNA:protein ratio, the myofibre density, and the percentage of small myofibres (0–150 µm2) decreased towards the end of the production cycle. However, small myofibres persisted even after the first 20 months of rearing. Compared with commonly cultivated species in the Mediterranean region, meagre exhibits delayed onset of puberty, larger ultimate size, and growth rate that is supported by the recruitment of new muscle fibres. This is in agreement with the hypothesis of a relationship between ultimate size and muscle growth dynamics.

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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.028
GPT teacher head0.198
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

Citations8
Published2012
Admission routes1
Has abstractyes

Explore more

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