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Chromosomal analysis of two buffalo breeds of Mazani and Azeri from Iran

2015· article· en· W2278760242 on OpenAlexaff
Mostafa Pournourali, Alireza Tarang, Farhad Mashayekhi

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsBiotechnology Research Institute
Fundersnot available
KeywordsKaryotypeGiemsa stainChromosomePloidyBiologyMetaphaseGeneticsChromosome numberVeterinary medicineMedicineGene

Abstract

fetched live from OpenAlex

In the present study karyotype of Mazani river buffalo was studied in comparison with those of Azeri buffalo populations from Iran. Blood samples were taken from ten (5 males and 5 females) Mazani buffaloes and thirty (15 males and 15 females) Azeri buffaloes. The Mazani buffaloes belong to Mazendaran province and Azeri buffaloes belong to west and east Azerbaijan and Ardebil provinces. Blood lymphocytes cultured at 37ºC for 72 hours in the presence of phytohemagglutinin and the metaphase spreads were performed on microscopic slide. Giemsa was used to stain chromosomes. The Mazani and Azeri Buffalo exhibited the same karyotype with diploid number of 2n = 50. The fundamental numbers (NF) were 60 in male and female. The types of chromosome were 6 submetacentric, 4 metacentric and 40 telocentric which the X chromosome is the largest telocentric and the Y chromosome is one of the smallest telocentric chromosomes. The relative length of chromosomes ranged between 2.17% to 7.2% in Mazani buffalo, and also 2.21% to 6.55% in Azeri buffalo. No obvious abnormality was found among chromosomes. Therefore, based on the identified karyotype both Mazani and Azeri buffaloes are riverine.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

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 head0.187
GPT teacher head0.500
Teacher spread0.312 · 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 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

Citations4
Published2015
Admission routes1
Has abstractyes

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