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Record W2510068665 · doi:10.1039/c6em00395h

Concentrations, gas–particle distributions, and source indicator analysis of brominated flame retardants in air at Toolik Lake, Arctic Alaska

2016· article· en· W2510068665 on OpenAlexaff
Cleo L. Davie‐Martin, Kimberly J. Hageman, Yu‐Ping Chin, Benjamin Nistor, Hayley Hung

Bibliographic record

VenueEnvironmental Science Processes & Impacts · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsToronto Public HealthEnvironment and Climate Change Canada
FundersUniversity of OtagoNational Science Foundation
KeywordsArcticEnvironmental scienceThe arcticParticle (ecology)Environmental chemistryAtmospheric sciencesOceanographyChemistryGeology

Abstract

fetched live from OpenAlex

Brominated flame-retardants (BFRs) can be released from consumer products, resulting in accumulation in the surrounding environment and/or long-range transport to remote environments. We evaluated concentration changes in a suite of BFRs, including 13 polybrominated diphenyl ethers (PBDEs) and 1,2-bis(2,4,6-tribromophenoxy)ethane (BTBPE), in air at Toolik Lake, Arctic Alaska during the Northern Hemisphere summer of 2013. A high-volume active air sampler was used to collect 2 day integrated samples at the field station and three flow-through air samplers were used to collect 18 day integrated samples along a transect extending away from the field station. The BDE congeners associated with the penta-BDE commercial mixture (BDE-47, -99, and -100) were the most frequently detected BFRs and were found at concentrations consistent with those reported at other Arctic sites. Gas-particle distributions were influenced by temperature and correlations between gas-phase concentrations and temperature suggested that either volatilization from local sources or re-emission from secondary sources (that is, re-volatilization of BFRs that had migrated northwards from distant sources) was important for the lower-brominated BFRs during the warmer months. Source indicator analysis suggested no single dominant geographic source of BFRs while results from the flow-through samplers indicated that the field station itself was not a significant source of BFRs.

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 score0.252
Threshold uncertainty score0.500

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 studies0.0010.000
Scholarly communication0.0010.000
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 head0.005
GPT teacher head0.217
Teacher spread0.212 · 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

Citations10
Published2016
Admission routes1
Has abstractyes

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