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Tire-derived compounds, phthalates, and trace metals in the Kiel Fjord (Germany)

2025· article· en· W4406767813 on OpenAlexaff
Michael Lintner, Charlotte Henkel, Ruoting Peng, Petra Heinz, Martin Stockhausen, Thilo Hofmann, Thorsten Hüffer, Nina Keul

Bibliographic record

VenueMarine Pollution Bulletin · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsMcGill University
FundersHORIZON EUROPE Marie Sklodowska-Curie ActionsH2020 Marie Skłodowska-Curie ActionsNarodowe Centrum NaukiAustrian Science Fund
KeywordsFjordEnvironmental chemistryEnvironmental scienceTRACE (psycholinguistics)OceanographyChemistryGeology

Abstract

fetched live from OpenAlex

Concerns about pollutants in the environment are increasing, with substances such as plastic additives drawing particular concern due to their potential harmful effects on organisms. This study investigates current levels of several contaminants in the Kiel Fjord. Some pose serious health risks to aquatic life. In September 2022, water and sediment samples were collected from fifteen stations across the inner and outer Kiel Fjord. The concentrations of selected phthalates, tire-derived compounds, and heavy metals were measured. Results indicate that the outer fjord has minimal contamination, while the inner fjord contains several hotspots with significant pollutant concentrations. For example, the highest levels of heavy metals were detected near Laboe and in deeper sediment layers (>6 cm) at Wik. The maximum concentrations of phthalates were observed near Laboe, with elevated levels also found near the city of Kiel and the Nord-Ostsee-Kanal. This study highlights the substantial anthropogenic impact on the region.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.422

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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