MétaCan
Menu
Back to cohort
Record W2086885850 · doi:10.1080/19443994.2013.821954

Bioaccumulation of heavy metals in the Cyprinus carpio organs of the El Izdihar dam (Algeria)

2013· article· en· W2086885850 on OpenAlexfundno aff
Zineb Derrag, Nacéra Dali Youcef

Bibliographic record

VenueDesalination and Water Treatment · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
FundersNational Research Council CanadaUniversity of Tlemcen
KeywordsBioaccumulationGillCyprinusEnvironmental chemistryChemistryAtomic absorption spectroscopyZincAnimal scienceFisheryBiologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

AbstractThe objective of this study is to determine the bioaccumulation of heavy metals in different organs of Cyprinus carpio of El Izdihar dam, Sidi Abdelli (Wilaya of Tlemcen) in northwestern Algeria. This latter is an important water resource for drinking water and irrigation in the region. The Zn, Pb, Fe, Ni, Cu, and Cd elements were analyzed using the Rayleigh WFX-130 atomic absorption spectrophotometer after wet digestion by Malayandi and Barette method. The results are given in mg/kg dry weight. One way ANOVA and principal component analysis (PAC) were used to compare the data among months (levels of 0.05). Mean concentrations were found to decrease in C. carpio samples in sequence in gills and gonads as Zn > Fe > Pb > Ni > Cu > Cd, in fillets as Zn > Pb > Ni > Fe > Cu > Cd. For Zn and Fe, bioaccumulation in the gills is higher than in the gonads and fillets. For Cu and Cd: fillets > gills > gonads, and for Pb and Ni: fillets > gonads > gills. In fish samples, the concentrations of zinc, lead, and...

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.245
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2013
Admission routes1
Has abstractno

Explore more

Same venueDesalination and Water TreatmentSame topicHeavy metals in environmentFrench-language works237,207