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Record W2170427749 · doi:10.1002/jez.a.10318

Muscle enzyme activities in a deep‐sea squaloid shark, <i>Centroscyllium fabricii</i>, compared with its shallow‐living relative, <i>Squalus acanthias</i>

2003· article· en· W2170427749 on OpenAlexafffund
Jason R. Treberg, Ralph Martin, William R. Driedzic

Bibliographic record

VenueJournal of Experimental Zoology Part A Comparative Experimental Biology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicIchthyology and Marine Biology
Canadian institutionsQuest University CanadaMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSqualus acanthiasLactate dehydrogenaseCreatine kinaseBiologyGlycolysisInternal medicineEnzymeAnatomyEndocrinologyBiochemistryMedicine

Abstract

fetched live from OpenAlex

The activities of several enzymes of energy metabolism were measured in the heart, red muscle, and white muscle of a deep and a shallow living squaloid shark, Centroscyllium fabricii and Squalus acanthias, respectively. The phylogenetic closeness of these species, combined with their active predatory nature, similar body form, and size makes them well matched for comparison. This is the first time such a comparison has been made involving a deep-sea elasmobranch. Enzyme activities were similar in the heart, but generally lower in the red muscle of C. fabricii. Paralleling the trend seen in deep-sea teleosts, the white muscle of C. fabricii had substantially lower activities of key glycolytic enzymes, pyruvate kinase and lactate dehydrogenase, relative to S. acanthias or other shallow living elasmobranchs. Unexpectedly, between the squaloid sharks examined, creatine phosphokinase activity was higher in all tissues of the deep living C. fabricii. Low white muscle glycolytic enzyme activities in the deep-sea species coupled with high creatine phosphokinase activity suggests that the capacity for short burst swimming is likely limited once creatine phosphate supplies have been exhausted.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.067
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.027
GPT teacher head0.289
Teacher spread0.262 · 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 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

Citations34
Published2003
Admission routes2
Has abstractyes

Explore more

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