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Record W2965598308 · doi:10.5539/sar.v8n3p49

Poultry Production System in Mauritania before the Activities of the “Program to Alleviate Rural Poverty through Support to Subsectors” (ProLPRAF)

2019· article· en· W2965598308 on OpenAlexvenueno aff
Salimata Pousga, Cheikh Ben Maali, Georges Anicet Ouédraogo

Bibliographic record

VenueSustainable Agriculture Research · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLivestock and Poultry Management
Canadian institutionsnot available
Fundersnot available
KeywordsPoultry farmingAgricultural scienceAgricultureProduction (economics)PovertyGeographyBroilerPoultry meatAgricultural economicsSocioeconomicsBiologyVeterinary medicineBusinessEconomic growthAnimal scienceEconomicsForestryFood science

Abstract

fetched live from OpenAlex

The objective of the present study was to display the state of poultry production in fourth (4) regions (Nouakchott, Hodh El Gharbi, Assaba and Guidimaka) covered by ProLPRAF program at the beginning of the program activities in 2011. Data were collected during surveys with different questionnaires addressed to different actors of the poultry sector. Results from farmers showed that 65.0% were female with average age of 45.3 ± 8.40 years. Production constraints remained the same as those encountered in poultry farming in developing countries. There were no poultry markets in the regions, poultry sellers in Nouakchott were male (100%) with average age of 34.8 ± 5.2 years. Traditional local chicken marketed in the regions came either from Nouakchott region (40%) and others (40%), or imported from neighboring countries (20%). In modern poultry farming, day-old chick was imported from Morocco (85%) or Senegal (15%) as well as production inputs. The price of local chicken ranged from 1385 ± 126 to 2325 ± 275 MU, while broiler chicken was between 1255 ± 60 and 1470 ± 47 MU. Local chicken was for ritual, traditions and practices (75%). Layer’s Eggs were imported from Morocco (55%) or Senegal (45%), and average unit price of one egg was around 43.0 ± 5.0 MU. Poultry meat cooked in the restaurants consisted exclusively of broilers meat (100%). Poultry farming was facing socio-political constraints that limited its development, but the ProLPRAF program has been able to tackle these constraints and the impact of the program is plausible today.

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)0.001
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 score0.303
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.015
GPT teacher head0.275
Teacher spread0.260 · 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
Published2019
Admission routes1
Has abstractyes

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