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Record W2809915450 · doi:10.1007/s11356-018-2603-0

Bio-concentration potential and associations of heavy metals in Amanita muscaria (L.) Lam. from northern regions of Poland

2018· article· en· W2809915450 on OpenAlexaff
Jerzy Falandysz, Małgorzata Mędyk, Roland Treu

Bibliographic record

VenueEnvironmental Science and Pollution Research · 2018
Typearticle
Languageen
FieldMedicine
TopicFungal Biology and Applications
Canadian institutionsAthabasca University
Fundersnot available
KeywordsBioconcentrationAmanitaMyceliumEnvironmental chemistryMetalChemistryTopsoilEcotoxicologyMushroomSoil waterBotanyBioaccumulationEcologyBiologyFood science

Abstract

fetched live from OpenAlex

Fruiting bodies of Amanita muscaria and topsoil beneath from six background areas in northern regions of Poland were investigated for the concentration levels of Ag, Al, Ba, Ca, Cd, Co, Cu, Fe, Hg, K, Mg, Mn, Na, Rb, Sr, and Zn. In addition, the bioconcentration factors (BCF values) were studied for each of these metallic elements. Similar to studies from other basidiomycetes, A. muscaria showed species-specific affinities to some elements, resulting in their bioconcentration in mycelium and fruiting bodies. This mushroom growing in soils with different levels of the geogenic metallic elements (Ag, Al, Ba, Ca, Co, Cu, Fe, Hg, K, Mg, Mn, Na, Rb, Sr, and Zn) showed signs of homeostatic accumulation in fruiting bodies of several of these elements, while Cd appeared to be accumulated at a rate dependent of the concentration level in the soil substrate. This species is an efficient bio-concentrator of K, Mg, Cd, Cu, Hg, Rb, and Zn and hence also contributes to the natural cycling of these metallic elements in forest ecosystems.

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 score0.003
Threshold uncertainty score0.006

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)0.0000.000

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 head0.037
GPT teacher head0.334
Teacher spread0.297 · 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

Citations41
Published2018
Admission routes1
Has abstractyes

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