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Record W3156879733 · doi:10.3996/jfwm-20-044

Blood Lead Declines in Wintering American Black Ducks in New Jersey Following the Lead Shot Ban

2021· article· en· W3156879733 on OpenAlexaboutno aff
Nicole L. Lewis, Theodore C. Nichols, Christina Lilley, Douglas E. Roscoe, Jan Lovy

Bibliographic record

VenueJournal of Fish and Wildlife Management · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsWaterfowlShot (pellet)Lead poisoningLead exposureFlywayLead (geology)AnasFisheryBlood lead levelAnatidaeAythyaGeographyEcologyBiologyMedicineHabitatChemistry

Abstract

fetched live from OpenAlex

Abstract Waterfowl managers first recognized the problem of lead poisoning in ducks from the ingestion of spent lead shot (pellets) over 100 years ago. The phaseout of lead shot for waterfowl hunting began in the Atlantic Flyway in the 1970s. Lead shot was subsequently banned throughout the United States and Canada prior to 2000. We compared blood lead levels in American black ducks Anas rubripes wintering in coastal New Jersey in 1978, prior to the lead ban, and in 2017, about 39 years after lead shot was first banned for use in Atlantic coastal marshes and 27 years after it was banned for waterfowl hunting in New Jersey. The prevalence of blood lead >0.2 ppm, a level commonly used to indicate lead exposure, declined nearly fourfold from 1978 (79%) to 2017 (20%). We found no significant differences in the prevalence of birds with blood lead levels >0.2 ppm between sexes in either year or between age classes in 2017. The prevalence of ducks with blood lead levels >1.0 ppm, considered clinically evident toxicity, declined from 19% in 1978 to 1% in 2017. Our study provides further evidence that the ban on the use of lead shot over 20 years ago throughout North America has resulted in lower blood lead levels in waterfowl. Notwithstanding, we still found evidence of lead exposure in black ducks in 2017, which warrants further investigation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.066
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.025
GPT teacher head0.274
Teacher spread0.249 · 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 teacher head, 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

Citations11
Published2021
Admission routes1
Has abstractyes

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