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Record W2885293774 · doi:10.1002/jms.4283

Discrimination of wild and domestic deer musk using isotope ratio mass spectrometry

2018· article· en· W2885293774 on OpenAlexfundno aff
Yi He, Jingzhu Wang, M. Wang, Jingfang Zhang

Bibliographic record

VenueJournal of Mass Spectrometry · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
FundersWorld Anti-Doping Agency
KeywordsChemistrySteroidGas chromatography–mass spectrometryMass spectrometryZoologyChromatographyBiologyBiochemistryHormone

Abstract

fetched live from OpenAlex

Abstract Musk is the dried secretion of the musk pod (sac) of adult male musk deer, and has been used as perfume and traditional medicine for thousands of years. Steroid was regarded as 1 of the most important active compounds in musk. In order to protect the wild musk deer, musk deer farming has been carried out in China, India, and Nepal. However, it is hard to differentiate the 2 origins of musk by morphological identification. No other method has been reported so far for the discrimination of wild and domestic deer musk. The establishment of a reliable discrimination method has become an urgent work. In the present study, 6 batches of wild deer musk and 14 batches of domestic deer musk were collected. Analysis of steroid components in musk was carried out with GC‐MS/MS. Androgen, progestin, estrogen, and sterol were detected in those samples. Large diversity was observed in the concentrations of steroids in musk. No obvious difference could be observed in steroid concentrations between wild and domestic deer musk by principal component analysis and cluster analysis. Furthermore, the δ 13 C values of steroids were determined by gas chromatography/combustion coupled with isotopic ratio mass spectrometry. There were significant differences ( P < .01) in steroid δ 13 C values between wild origin musk and domesticated origin musk. Isotopic ratio mass spectrometry can be used to discriminate wild and domestic deer musk.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.251
Teacher spread0.237 · 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 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

Citations12
Published2018
Admission routes1
Has abstractyes

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