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Record W2370448777

Relationship Between Subclinic Mastitis and the Concentration of Trace Element Zn,Cu and Mn in Cow Hair

2005· article· en· W2370448777 on OpenAlexaboutno aff
Shang Chang-fa

Bibliographic record

VenueProgress in Veterinary Medicine · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsnot available
Fundersnot available
KeywordsMastitisQuarter (Canadian coin)Animal scienceAtomic absorption spectroscopySignificant differenceTrace elementVeterinary medicineChemistryBiologyInternal medicineMedicineMicrobiologyGeography
DOInot available

Abstract

fetched live from OpenAlex

In order to study the relation between subclinic mastitis and trace element in cow hair,50 cows were selected and divided into 5 groups:only one quarter have subclinic mastitis(Ⅰ),two quarter have subclinic mastitis(Ⅱ),three quarter have subclinic mastitis(Ⅲ),four quarter have subclinic mastitis(Ⅳ)and the control group have not mastitis(Ⅴ). The content of Zn,Cu,Mn in hair were tested by the spectrometry atomic absorption. The results showed that concentration of Zn,Cu,Mn in group Ⅰ had significant difference with group Ⅲ(P0.05).None of the other groups had significant difference each other(P0.05).

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.039
GPT teacher head0.323
Teacher spread0.284 · 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 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

Citations0
Published2005
Admission routes1
Has abstractyes

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