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Record W2894956078 · doi:10.1007/s11356-018-3336-9

Distribution of organic and inorganic mercury in the tissues and organs of fish from the southern Baltic Sea

2018· article· en· W2894956078 on OpenAlexfundno aff
Lucyna Polak-Juszczak

Bibliographic record

VenueEnvironmental Science and Pollution Research · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
FundersNational Research Council CanadaFundacja na rzecz Nauki Polskiej
KeywordsBiomagnificationSpratBioaccumulationTrophic levelMercury (programming language)HerringMethylmercuryBiologyPredatory fishFood chainFood webZoologyPredationFisheryEcologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The aim of this study was to determine the distribution of total mercury (THg), methylmercury (CH3Hg+), and inorganic mercury (Hginorg) in the tissues and organs of fish depending on species, tissue, and organ, and their bioaccumulation in tissues and biomagnification throughout the trophic web. The study included four species of fish (herring, sprat, cod, and eel) from the southern Baltic Sea. The concentrations of the different forms of mercury were determined in tissues and internal organs. Intra-specific differences in levels of THg, CH3Hg+, and Hginorg in the tissues and organs were determined. Muscle contained the highest proportions of THg and CH3Hg+ in comparison to that in the internal organs. Differences in concentrations of THg, CH3Hg+, and Hginorg in the tissues and organs of fish were related to their preferred prey. The bioaccumulation of CH3Hg+ in the tissues and organs of predatory fish at the highest trophic levels was greater than in the liver and digestive tract of fish species at lower trophic levels, in which Hginorg predominated. The high concentrations of CH3Hg+ in eel and cod and the low levels in herring and sprat were linked with their food and the transfer of this element among species. The results suggested that the type of food, feeding habits, and trophic position were important parameters that influenced the transfer and biomagnification of mercury in fish.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.006
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 head0.026
GPT teacher head0.299
Teacher spread0.273 · 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.

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

Citations53
Published2018
Admission routes1
Has abstractyes

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