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Record W4322628239 · doi:10.1016/j.heliyon.2023.e14031

Nutritional composition, heavy metal contents and lipid quality of five marine fish species from Cameroon coast

2023· article· en· W4322628239 on OpenAlexfundno aff
J.C.K. Manz, Jean Valery François Nsoga, J.B. Diazenza, S. Sita, G.M.B. Bakana, Allal. François, Mathieu Ndomou, I. Gouado, Victor Mamonékéné

Bibliographic record

VenueHeliyon · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFish Biology and Ecology Studies
Canadian institutionsnot available
FundersRural Development AdministrationAgence Universitaire de la Francophonie
KeywordsCyprinusSardinellaComposition (language)BiologyFisheryFish <Actinopterygii>Food scienceChemistrySardine

Abstract

fetched live from OpenAlex

The nutritional value, heavy metal content and lipid quality of five marine fishes from, Cameroon coast were be investigated. Fish samples from Ilisha africana, Sardinella, maderensis, Cyprinus carpio , Arius parkii and Ethmalosa fimbriata were collected at, the Douala sea port, carried to the laboratory, washed with distilled water and, processed. Proximal composition, minerals, lipid quality and heavy metal analyses, were performed using AOAC standard methods. Results show that proteins (18.43%), and lipids (3.69%) contents were higher in Ilisha africana. Cyprinus carpio had the, highest ash content (4.59%). Contents of minerals and heavy metals were found as, follows: P > Mg > K > Ca > Na > Fe > Zn > Cu > Mn and Hg > Pb > Cd > As. Oils extracted from C. carpio , A. parkii and E. fimbriata were semi-siccative while those of I. africana and S. maderensis were siccative. Thus, these fish species are good sources of proteins and, minerals that can be used for managing mineral deficiencies in humans and animals.

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)0.000
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 score0.242
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.049
GPT teacher head0.251
Teacher spread0.202 · 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

Citations22
Published2023
Admission routes1
Has abstractyes

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