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Record W7096344420

2005): Subclinical mastitis in buffaloes in attock district of Punjab (Pakistan). Pakistan Vet

2015· article· en· W7096344420 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsnot available
Fundersnot available
KeywordsMastitisCalifornia mastitis testQuarter (Canadian coin)PrevalenceEpidemiologySubclinical infectionDairy cattle
DOInot available

Abstract

fetched live from OpenAlex

Mastitis is the most costly disease of dairy industry throughout the world. Sub-clinical mastitis is not observed by the farmers but results in hidden losses in terms of production. The present study was conducted to determine the quarter wise and animal wise prevalence of sub-clinical mastitis in buffaloes in Attock district of Punjab, Pakistan. Milk samples were collected from apparently mastitis free 1200 quarters of 300 buffaloes. The samples were subjected to Surf Field Mastitis Test (SFMT). The overall quarter wise prevalence was 58.75 percent, while animal wise prevalence was 77.98 percent. The maximum quarter wise prevalence was found to be 16.66 percent in Tehsil Jand, followed by 13.33, 11.67 and 13.33 percent in the tehsils Attock, Pindighaib, and Fateh Jang, respectively. The maximum animal wise prevalence was 82.61 percent in Tehsil Pindighaib, followed by 73.33, 80.00 and 76.00 percent in the tehsils Attock, Jand and Fateh Jang, respectively.

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 score0.025
Threshold uncertainty score0.050

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 studies0.0010.001
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 head0.070
GPT teacher head0.321
Teacher spread0.250 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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