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Record W2053743835 · doi:10.1021/es062352x

Polychlorinated Naphthalenes in the Global Atmospheric Passive Sampling (GAPS) Study

2007· article· en· W2053743835 on OpenAlexaff
Sum Chi Lee, Tom Harner, Karla Pozo, Mahiba Shoeib, Frank Wania, Derek C. G. Muir, Leonard A. Barrie, Kevin C. Jones

Bibliographic record

VenueEnvironmental Science & Technology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsCombustionEnvironmental scienceEnvironmental chemistrySampling (signal processing)Passive samplingAtmospheric sciencesAir pollutionChemistryMathematicsStatisticsGeology

Abstract

fetched live from OpenAlex

Air concentrations of polychlorinated naphthalenes (PCNs) were measured as part of the Global Atmospheric Passive Sampling (GAPS) study to assess their spatial distribution on a worldwide basis for the first sampling period between December 2004 and March 2005. Results from more than 40 sites on seven continents show that PCNs are widespread, and highest levels are detected in urban/industrial locations consistent with other air sampling studies. The geometric mean air concentration of sigmaPCN is 1.6 pg/m3, ranging from below detection limit to 32 pg/m3. With technical PCN mixtures largely no longer produced, combustion inputs may be contributing increasingly to contemporary PCN air burden globally. Enrichment of combustion-related congeners, e.g., PCN-52/60, -50, -51,-54, and -66/67, is observed in the congeneric compositions of air at nearly all sites compared to relatively minor contribution of these congeners in technical PCN formulations. Further evidence of current combustion sources influencing global PCN levels is a higher relative abundance of combustion-related congeners quantified by sigmaPCNcombustion/sigmaPCN. The relative contribution by combustion sources and emissions from technical PCN mixtures is expected to vary among sites since it depends on the combustion sources and the technical mixture used in a particular country or region.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.008
GPT teacher head0.261
Teacher spread0.253 · 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.

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

Citations121
Published2007
Admission routes1
Has abstractyes

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