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Record W1959486344 · doi:10.1007/s13280-015-0673-5

Temporal and spatial trends of PCBs, DDTs, HCHs, and HCB in Swedish marine biota 1969–2012

2015· article· en· W1959486344 on OpenAlexaff
Elisabeth Nyberg, Suzanne Faxneld, Sara Danielsson, Ulla Eriksson, Aroha Miller, Anders Bignert

Bibliographic record

VenueAMBIO · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsUniversity of British Columbia
FundersNaturvårdsverket
KeywordsBiotaClupeaGadusHerringBaltic seaMytilusUria aalgeBiomagnificationFisheryBiologyHerring gullEnvironmental chemistryEnvironmental scienceEcologyBioaccumulationOceanographyFish <Actinopterygii>PredationChemistryLarus

Abstract

fetched live from OpenAlex

In the 1960s, the Baltic Sea was severely polluted by organic contaminants such as PCBs, HCHs, HCB, and DDTs. Elevated concentrations caused severe adverse effects in Baltic biota. Since then, these substances have been monitored temporally and spatially in Baltic biota, primarily in herring (Clupea harengus) and in guillemot (Uria aalge) egg, but also in cod (Gadus morhua), perch (Perca fluviatilis), eelpout (Zoarces viviparous), and blue mussel (Mytilus edulis). These chemicals were banned in Sweden in the late 1970s/early 1980s. Since the start of monitoring, overall significant decreases of about 70-90 % have been observed. However, concentrations are still higher in the Baltic Sea than in, for example, the North Sea. CB-118 and DDE exceed the suggested target concentrations (24 µg kg(-1) lipid weight and 5 µg kg(-1) wet weight, respectively) at certain sites in some of the monitored species, showing that concentrations may still be too high to protect the most sensitive organisms.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.233
Teacher spread0.219 · 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

Citations54
Published2015
Admission routes1
Has abstractyes

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Same venueAMBIOSame topicToxic Organic Pollutants ImpactFrench-language works237,207