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Record W2072758139 · doi:10.1667/rr2820.1

Fatty Acid Composition of Muscle Tissue Measured in Amphibians Living in Radiologically Contaminated and Non-Contaminated Environments

2012· article· en· W2072758139 on OpenAlexaff
M. Audette-Stuart, Carla Ferreri, Amy Festarini, James A. Carr

Bibliographic record

VenueRadiation Research · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsContaminationEnvironmental chemistryComposition (language)BiologyMuscle tissueChemistryAnatomyEcology

Abstract

fetched live from OpenAlex

Fatty acid composition was identified as a potential biological indicator of the effects of environmental exposure to radiological contaminants. This end point was measured in muscle tissues of Mink frogs ( Rana septentrionalis ) obtained from a radiologically contaminated pond and from a non-contaminated pond. It was also measured after the frogs obtained from both ponds were exposed to a 4 Gy (60)Co γ radiation dose delivered in vivo at a dose rate of approximately 8 Gy/min. Statistically significant differences for the increase of a couple of polyunsaturated omega-3 fatty acid residues and the decrease of a polyunsaturated omega-6 fatty acid residue were observed between radiologically contaminated and non-contaminated frogs, indicating a partial remodeling of muscle lipids in response to a chronic low-dose tritium exposure. The effects of an acute high-dose exposure to (60)Co γ radiation, either for the radiologically contaminated or non-contaminated frogs indicated fast post-irradiation fatty acid changes with an increase of polyunsaturated and decrease of saturated fatty acid contents. Fatty acid composition was found to be a sensitive marker that may be useful to study and monitor biota health in environments that are radiologically contaminated, as well as for understanding the differences between low chronic and high acute stress responses.

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 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 score0.560
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.025
GPT teacher head0.303
Teacher spread0.279 · 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

Citations12
Published2012
Admission routes1
Has abstractyes

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