MétaCan
Menu
← Back to cohort
Record W3117157461 · doi:10.23860/robuck-anna-2020

DISTRIBUTION OF NOVEL AND LEGACY ORGANIC POLLUTANTS IN SEABIRDS FROM CONTRASTING MARINE ENVIRONMENTS

2020· dissertation· en· W3117157461 on OpenAlexfundno aff
Anna R. Robuck

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsnot available
FundersNational Institute of Environmental Health SciencesNatural Sciences and Engineering Research Council of CanadaOak Ridge Institute for Science and EducationNational Oceanic and Atmospheric AdministrationKillam TrustsDalhousie UniversityRoyal SocietyRobert and Patricia Switzer Foundation
KeywordsPollutantExtant taxonEnvironmental scienceDistribution (mathematics)EcologyEnvironmental resource managementGeographyBiology

Abstract

fetched live from OpenAlex

Despite their ubiquity in the environment, large data gaps exist surrounding the distribution, biotic accumulation, and possible impacts of many high priority organic pollutants, particularly those considered emerging contaminants. Emerging pollutants, or contaminants of emerging concern (CECs), represent a dynamic and rapidly evolving group of substances, some of which have been extant for decades. Chapter 1 provides background about CECs covered in this dissertation, and highlights key data gaps explored within this work. The first three manuscripts of this dissertation (Chapters 2 – 5) focus on per- and polyfluoroalkyl substances, or PFAS. PFAS are a family of CECs that demonstrate amphiphilic or hydrophilic environmental behaviors, and thus are ubiquitously distributed in aqueous and biological matrices. PFAS are associated with adverse effects in humans and wildlife at very low concentrations, and thus their biological behavior and impacts are under a great deal of scrutiny. Little work over the past two decades has evaluated these chemicals in marine food webs along the US East Coast, despite the proximity of this region to major human population centers and PFAS point sources. Tandem mass spectrometry and high-resolution mass spectrometry techniques were applied to tissue samples collected as part of a large-scale necropsy program to derive PFAS measurements in seabirds from the US East Coast. Names, Chemical Abstracts Service (CAS) number, and potential sources of each PFAS measured in this work are provided in Appendix B. Chapter Two measured PFAS in seabird juveniles from three habitats along the US East Coast representing a range of exposure potential. Seabirds collected downstream from a major fluoropolymer production site contained the highest concentrations of legacy and novel PFAS, surpassing toxicity reference values established in controlled studies for avifauna. The novel PFAS Nafion by-product 2 (Nafion BP2) was detected in seabirds from all habitats, marking the first identification of this compound in biota beyond the industrially influenced Cape Fear region in North Carolina. Perfluorooctanesulfonic acid (PFOS) and perfluorononanoic acid (PFNA) were associated with decreased phospholipid levels, marking the first time this trend has been observed in a wild population. Chapter Three examined novel and legacy PFAS in Great Shearwaters from Massachusetts Bay over 2010 – 2019. PFOS and perfluorooctanesulfonamide (FOSA) decreased over the time series, while perfluoroalkyl carboxylic acids (PFCAs) and the novel PFAS 7:3 fluorotelomer carboxylic acid (7:3 FTCA) showed no clear trends over time. Multiple PFAS were significantly associated with morphometric variables, with increased PFAS levels associated

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: Other · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.014

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 communication0.0010.000
Open science0.0000.000
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 head0.014
GPT teacher head0.252
Teacher spread0.238 · 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
GenreOther

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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicPer- and polyfluoroalkyl substances research→French-language works237,207→