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Record W2312921058 · doi:10.5897/ajar2015.10408

Diversity and seasonal distribution of parasites of Oreochromis niloticus in semi-arid reservoirs (West Africa, Burkina Faso)

2016· article· en· W2312921058 on OpenAlexfundno aff
Sinar eacute Yamba, Boungou Magloire, Ou eacute da Adama, Gn eacute m eacute Awa, Boureima Kabr eacute Gustave

Bibliographic record

VenueAfrican Journal of Agricultural Research · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsnot available
FundersAgence Universitaire de la Francophonie
KeywordsOreochromisWet seasonAbundance (ecology)BiologyVeterinary medicineDry seasonEcologyFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

This study aimed to investigate the diversity, abundance, intensity, and seasonal distribution of parasites of Oreochromis niloticus. A total of 254 specimens of O. niloticus was sampled in Loumbila and Ziga reservoirs in both rainy and dry season and examined for parasites. The total prevalence was 55.90% and the highest seasonal prevalence, abundance and intensity were observed during the rainy season. Recorded parasites were the myxozoan Myxobolus tilapiae, the copepode Lamproglena monodi, the monogeneans Cichlidogyrus tilapiae, Cichlidogyrus halli, the digenetic trematode Clinostomum species, the nematode Paracamallanus cyathopharynx, and the acanthocephalan Acanthogyrus tilapiae. The latter species had higher prevalence (45.67%) and high abundance. L. monodi, C. tilapiae, C. halli, and P. cyathopharynx were only observed in Loumbila reservoir. A. tilapiae, Clinostomum spp. and M. tilapiae were found in both reservoirs with a high abundance.&nbsp;In conclusion, it was found out that O. niloticus specimens were heavy infection with a broad number of parasites. This situation could eventually reduce performance and productivity of the species, especially in aquaculture. Key words: Oreochromis niloticus, parasites, Loumbila reservoir, Ziga reservoir, Burkina Faso.

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)0.001
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 score0.120
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.040
GPT teacher head0.326
Teacher spread0.286 · 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

Citations14
Published2016
Admission routes1
Has abstractyes

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