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Record W4382561137 · doi:10.1656/045.030.0208

Updated Data on Mercury and DDE in Striped Bass (Morone saxatilis) in Relation to Consumption Advisories for the Saint John River, New Brunswick, Canada

2023· article· en· W4382561137 on OpenAlexaffabout
Samuel N. Andrews, David Roth, Karen A. Kidd, Scott A. Pavey, Bethany Reinhart, Brian Hayden, Michael J. Dadswell, Tommi Linnansaari, R. Allen Curry

Bibliographic record

VenueNortheastern Naturalist · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsAcadia UniversitySaint John Regional HospitalMcMaster UniversityUniversity of New Brunswick
Fundersnot available
KeywordsOverfishingMercury (programming language)Bass (fish)FisheryMorone saxatilisMoronePopulationBiologyGeographyFish <Actinopterygii>Environmental healthMedicine

Abstract

fetched live from OpenAlex

The Morone saxatilis (Striped Bass) population in Saint John River (SJR), NB, Canada, collapsed in the 1970s concurrent with dam construction, overfishing, and chemical pollution that may have impeded reproduction. To assess whether a chemical threat to Striped Bass or a health threat to fish consumers persists, we examined DDT and total mercury (THg) levels from 29 Striped Bass captured in the SJR including 16 genomically typed as SJR natives. DDT and DDD in female gonads were below detectable levels, and DDE averaged 0.08 ± 0.09 mg/kg wet weight (ww) but was considered too low to threaten reproduction. Total mercury in muscle and liver varied from 0.68 to 2.10 mg/kg and 0.35 to 3.27 mg/kg ww, respectively and exceeded Health Canada guidelines in all samples. We suggest regulators should update advisories for consumption including actively informing the public of the risk.

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 score0.023
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.286
Teacher spread0.247 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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