MétaCan
Menu
Back to cohort
Record W2005462073 · doi:10.1039/b918998j

Polychlorinated biphenyls, organochlorine pesticides and polycyclic aromatic hydrocarbons in a one-off global survey of bivalves

2010· article· en· W2005462073 on OpenAlexaboutno aff
Katrin Vorkamp, Jakob Strand, Jan H. Christensen, Tore C. Svendsen, Pia Lassen, Asger B. Hansen, Martin Mørk Larsen, Ole Andersen

Bibliographic record

VenueJournal of Environmental Monitoring · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsnot available
Fundersnot available
KeywordsShetlandEnvironmental chemistryOrganochlorine pesticideEnvironmental sciencePesticideEstuaryPersistent organic pollutantPollutantGeographyEcologyChemistryOceanographyGeologyBiologyForestry

Abstract

fetched live from OpenAlex

During the Danish Galathea 3 expedition, bivalve samples were collected at the Faroe Islands, Greenland, Ghana, South Africa, Australia, Solomon Islands, New Zealand, Chile, US Virgin Islands, Boston, Newfoundland and Shetland Islands and analysed for organochlorines and PAHs. Concentration differences of up to three orders of magnitude were observed, with the highest concentrations at Boston harbour (SPCB 338 ng g(-1) dw, ΣSPAH 5966 ng g(-1) dw) and the Sydney estuary (ΣSPCB 282 ng g(-1) dw, SPAH 1453 ng g(-1) dw). Local impacts were also found for the Greenland capital Nuuk in terms of PCB and PAH levels, while other Greenland samples came closest to representing PAH background levels. Several locations had undetectable organochlorine levels, including Hobart and Chile, which had the lowest SPAH concentrations (<200 ng g(-1) dw). It was possible to group the stations according to their pyrogenic/petrogenic influence using Principal Component Analyses, and indications of petroleum sources were found at Nuuk.

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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.015
GPT teacher head0.245
Teacher spread0.230 · 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

Citations29
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Environmental MonitoringSame topicToxic Organic Pollutants ImpactFrench-language works237,207