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The Incidence of Postpartum Metritis and Retained Placenta in Cattle and Buffalo Cows in some Villages Around Baghdad

2015· article· en· W2287734721 on OpenAlexvenueno aff
Al-Saed Abbas H. Naief, Azhar Ahmed Khazraji, N. N. Al-Anbari, Hameed Hasson Al-Saeidy, Hasan Abid Hasan

Bibliographic record

VenueJournal of Buffalo Science · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Diversity and Health Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMetritisRetained placentaVeterinary medicineBubalusIncidence (geometry)EndometritisAnimal scienceWater buffaloDairy cattleBiologyMedicinePregnancyPlacentaIce calvingFetusLactationEcology

Abstract

fetched live from OpenAlex

This survey aimed to investigate the incidence rate of some reproductive problems especially retained placenta and metritis in cattle and buffalo cows to design appropriate manners for correction and treatment of such disorders of those two important animals in Iraq. A field survey was carried out on 257 cattle cows during 2011 and 290 during 2012 and 383 local water buffalo cows (Bubalus bubalis), during 2011 and 404 during 2012 in some villages around Baghdad (Al-Fudalia, 7 Nisan and Basmaia) where animals were reared. A complete data about case history, owner complains, clinical examinations for reproductive status, were documented by private clinics during 2011 - 2012. Results revealed that retained placenta percentage in cattle was 12.84, 12.41% during 2011, 2012 respectively, whereas it was 12.53, 12.62% during 2011, 2012 respectively in buffalo cows, in the case of uterine infections percentages, buffalo exhibited the highest percentages (40.46,37.87 %) during 2011, 2012 respectively in the comparison with cattle which showed 35.40, 35.17 % during 2011,2012 respectively. Highly significant differences (p ≤ 0.01) between species were observed yearly and during some months during the years of study. We concluded that management programs differences and environmental changes may lead to monthly and yearly differences in reproductive disorders capability.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.019
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.042
GPT teacher head0.269
Teacher spread0.227 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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