MétaCan
Menu
Back to cohort
Record W4312528111 · doi:10.56093/ijans.v90i11.111496

Differential karyotype profiling of three popular breeds of dogs in India

2021· article· en· W4312528111 on OpenAlexaboutno aff
Yogeshwar Sandhu, SHASHIKANT MAHAJAN, R. S. Sethi, Jaspreet Singh Arora, Chandra Sekhar Mukhopadhyay

Bibliographic record

VenueThe Indian Journal of Animal Sciences · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicChromosomal and Genetic Variations
Canadian institutionsnot available
FundersGuru Angad Dev Veterinary and Animal Sciences UniversityDepartment of Biotechnology, Ministry of Science and Technology, India
KeywordsGiemsa stainKaryotypeBiologyMetaphaseG bandingBreedVeterinary medicineGerman Shepherd DogStainingAndrologyPathologyChromosomeGeneticsMedicineGene

Abstract

fetched live from OpenAlex

The present investigation aims to study the karyology of the three most popular dog breeds as well as indigenous local dog. In this study, we identified the most popular dog breeds of the Punjab region which are maintained as companion animals, or for guarding. Metaphase plates were prepared after culturing of lymphocytes isolated from heparinized blood collected from the identified three most popular canine breeds. The isolated lymphocyte cells were cultured for 70-72 h following the cell cycle arrest at metaphase. The G-banding of the chromosomes was done by Giemsa staining through a standard protocol. The most popular three breeds of dog in the sub-tropical region were Labrador, the German Shepherd, and Pug. There were no significant distinguishable differences between the karyotypes of the dog breeds studied. This study gives insight into karyology information, which can be beneficial to the researchers, dog breeders, and kennel clubs. Moreover, it provides information about chromosomal abnormalities which may lead to the study of various fertility, growth, and phenotypic abnormalities problems in dog breeds.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

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

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 head0.028
GPT teacher head0.241
Teacher spread0.212 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueThe Indian Journal of Animal SciencesSame topicChromosomal and Genetic VariationsFrench-language works237,207