MétaCan
Menu
Back to cohort
Record W2738210328 · doi:10.5539/jas.v9n8p43

Determination of Major and Minor Elements in Maltese Sheep, Goat and Cow Milk Using Microwave Plasma-Atomic Emission Spectrophotometry

2017· article· en· W2738210328 on OpenAlexvenueno aff
Ritianne Spiteri, Everaldo Attard

Bibliographic record

VenueJournal of Agricultural Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Diversity and Health Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRuminantSheep milkAnimal scienceCow milkChemistryFood scienceBiologyAgronomyCrop

Abstract

fetched live from OpenAlex

The mineral content of milk from sheep, goats and cows bred in Malta and Gozo were determined for the first time. Two hundred and twenty samples were collected from cow, sheep and goat farms in Malta and Gozo. Ten macro and micro minerals were analysed, using microwave plasma-atomic emission spectrophotometry.No significant differences were observed between localities for the metals in the ruminant milk. Three micro minerals, Mn, Cr and Cd were not detected in the three milk types. However, most metals differed significantly between ruminants. Potassium was highest in cow milk, while Ca was significantly the highest in sheep milk. The other metals occurred at much lower concentrations. For the micro minerals, sheep milk exhibited the highest concentrations for Fe, Mg and Cu while cow milk showed the highest values for Zn and Ba. Principal component analysis revealed the separation of the cow and sheep milk samples into two distinct clusters, while the goat milk samples were scattered across the two clusters. This shows the distinctiveness of the sheep milk over the other two milk types.

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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.032
GPT teacher head0.278
Teacher spread0.246 · 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

Citations10
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural ScienceSame topicAnimal Diversity and Health StudiesFrench-language works237,207