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The Reality of Buffalo Breeding in Basra Governorate

2017· article· en· W2605182474 on OpenAlexvenueno aff
Mudhar A. S. Abu Tabeekh, Hamed Abdul Majid Abdul Mohsen, Amal A. Al Jaberi

Bibliographic record

VenueJournal of Buffalo Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Diversity and Health Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyBiology

Abstract

fetched live from OpenAlex

Buffaloes in Iraq represent the most productive animal since its domestication in Mesopotamia about pre-historic era. Domestic water buffalo (Babalus Babalis) are common in the marshes of southern Iraq. On Sunday the UN cultural agency, UNESCO, added the marshlands and the ancient Sumerian cities that once flourished among them to its list of sites. The marshes today remain one of the poorest areas. Residents living on tiny floating islands fish, tend water buffalo and gather reeds. Little published research could be found into the numbers or environmental impacts of water buffalo in Basra governorate. One of the research objectives was to survey the water buffalo in this region including Al Dear, Al Hartha, Abu Alkhasib, Shat Alarab, Al Qurna, Al Mdainah, Imam Sadiq, Imam Qaim, Al Faw, Al Nshwa, Al Zubair and in Basra center. This study was conducted to evaluate all aspects of the river buffalo for the period from 2012-2016. Comprehensive knowledge of the breed characteristics, its population size and structure, taxonomy, geographical distribution and most important diseases is required to have effective management. As the marsh Arabs or Ma'adan complain of problems with some common buffalo diseases, such as those infecting the hoofs and the tongue, providing of veterinary services would be of critical value for buffalo breeding from an economical prospective.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.094
GPT teacher head0.307
Teacher spread0.213 · 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.

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

Citations3
Published2017
Admission routes1
Has abstractyes

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