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Record W4390698897 · doi:10.3389/fphys.2023.1229152

Utilizing NMR fecal metabolomics as a novel technique for detecting the physiological effects of food shortages in waterfowl

2024· article· en· W4390698897 on OpenAlexafffund
B. Murray, Karen L. Machin

Bibliographic record

VenueFrontiers in Physiology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsUniversity of Saskatchewan
FundersEnvironment and Climate Change Canada
KeywordsEconomic shortageWaterfowlMetabolomicsFecesFood shortageFood scienceBiologyBioinformaticsMicrobiologyEcology

Abstract

fetched live from OpenAlex

Metabolomics is the study of small, endogenous metabolites that participate in metabolic reactions, including responses to stressors. Anthropogenic and environmental changes that alter habitat and food supply can act as stressors in wild waterfowl. These alterations invoke a series of physiological processes to provide energy to restore homeostasis and increase survival. In this study, we utilized fecal metabolomics to measure metabolites and identify pathways related to a 6-day feed restriction in captive mallard ducks (Anas platyrhynchos, n = 9). Fecal samples were collected before (baseline) and during feed restriction (treatment). H1 Nuclear Magnetic Resonance (NMR) spectroscopy was performed to identify metabolites. We found that fecal metabolite profiles could be used to distinguish between the feed-restricted and baseline samples. We identified metabolites related to pathways for energy production and metabolism endpoints, and metabolites indicative of gut microbiota changes. We also demonstrated that mallard ducks could utilize endogenous reserves in times of limited caloric intake. Fecal metabolomics shows promise as a non-invasive novel tool in identifying and characterizing physiological responses associated with stressors in a captive wild bird species.

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 score0.000

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 head0.013
GPT teacher head0.260
Teacher spread0.247 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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Same venueFrontiers in Physiology→Same topicMetabolomics and Mass Spectrometry Studies→French-language works237,207→