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Record W2604718052 · doi:10.6000/1927-5129.2017.13.09

Correlation Estimates between Carcass Traits of Nili Ravi and Kundhi Buffalo

2017· article· en· W2604718052 on OpenAlex
Muhammad Siddiq Zardari, Hubdar Ali Kaleri, Rameez Raja Kaleri, Asma Kaleri, Abdul Kabir, Syed Ramazan Shah, Tahir Niaz, Azhar Hussain Kaleri, Amjad Jakhro

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLivestock Management and Performance Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsBreedCarcass weightBiologyAnimal scienceCorrelationBody weightVeterinary medicineMathematicsMedicineEndocrinology

Abstract

fetched live from OpenAlex

Present study was designed to estimates the correlation between carcass traits of Nili Ravi and Kundhi buffalo. The data for carcass traits of Nili Ravi and Kundhi buffalo was collected from Seven Star International Meat Processing Company Dhabeji at Thatta. In current study the data of total 100 animals of Kundhi and Nili Ravi breed were selected and divided into A, B, C and D group. In group A and C there were Kundhi and Nili Ravi male whereas, B and D females of both breeds respectively. The data including live body weight, carcass weight, dressing percentage and boneless weight of both breeds Kundhi and Nili Ravi were collected for the estimation of correlation.The results for correlation estimates of different carcass traits indicated that the correlation estimation were found positive and high among Nili Rave breed as compared to Kundhi breed, which shows that an increase in one carcass trait would increase the other carcass traits. It was concluded that Nili Ravi carcass traits are better expressed and produces more beef than Kundhi, while Kundhi male is better in beef production than the Nili Ravi female whereas Kundhi female produces low carcass yield.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.542
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.037
GPT teacher head0.259
Teacher spread0.222 · 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