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Record W7080123628 · doi:10.20372/nadre:17451

Assessment of Major Livestock Feed Resources, Feed Balance and Nutritional Value in Soddo District, East Gurage Zone, Central Ethiopia

2025· article· en· W7080123628 on OpenAlexaff

Bibliographic record

VenueNational Academic Digital Repository of Ethiopia · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsMinnow Environmental (Canada)
Fundersnot available
KeywordsLivestockAnimal husbandryPopulationAgricultureNatural resourceEconomic shortagePastureGrazingProduction (economics)

Abstract

fetched live from OpenAlex

The objective of this study was to assess livestock feed resource, feed balance and nutritional values at different agro ecologies of Soddo district, east Gurage zone, central Ethiopia. The kebeles of the district were stratified in to two agro- ecological zones and representative kebeles were selected from the two agro-ecology. .A total of 166 sampled respondents were selected by simple random sampling and data were collected by using semi- structure questionnaire interview and personal observation. The result of the study showed that the livestock production system in the district was a mixed crop-livestock production system. The overall family size per household was 6.72±0.27in high land agro ecology and 7.45±0.33in midland agro ecology , the average cattle population per household was 7.17±0.30 heads (6.84TLU), and the overall land holding was 1.29±0.325 ha per household in this study. . In the highland agro-ecology of the study areas, the major feed resources of cattle were crop residue, natural pasture, and Enset leaf while it was natural pasture and crop residue in midland agro-ecology. Annual feed supply in the district satisfies 68.9% and 79.7% TDM; 44.83% and 39.36% TDCP, and 69.46% and 83.25% TME of the maintenance requirement of livestock in TLU per year in highland and midland agro-ecologies, respectively. Major livestock constraints are shortage of feed, high-cost feed, inadequate extension and training service. Therefore, different intervention strategies are needed to improve the husbandry practices, mainly to improve the feed resource available and. Cattles feed deficit was serious problem and needs strong intervention and attention by the concerned bodies

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.694
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.255
Teacher spread0.244 · 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
Published2025
Admission routes1
Has abstractyes

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