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Record W2004593347 · doi:10.1021/es800479c

Levels and Isomer Profiles of Dechlorane Plus in Chinese Air

2008· article· en· W2004593347 on OpenAlexaff
Nanqi Ren, Ed Sverko, Yi-Fan Li, Zhang Zhi, Tom Harner, Degao Wang, Brian E. McCarry

Bibliographic record

VenueEnvironmental Science & Technology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsEnvironment and Climate Change Canada
FundersDalian Maritime UniversityChengdu University of TechnologyNortheast Forestry UniversityU.S. Environmental Protection Agency
KeywordsChinaEnvironmental scienceEnvironmental chemistryGeographyRural areaChemistryArchaeology

Abstract

fetched live from OpenAlex

The highly chlorinated flame retardant, Dechlorane Plus (DP), was measured in air across 97 Chinese urban and rural sites. DP was detected in 51 of these sites, with a mean air concentration in urban centers (15.6 +/- 15.1 pg m(-3)) approximately 5 times greater than those measured in rural areas (3.5 +/- 5.6 pg m(-3)). These DP levels were likely attributable to local sources rather than trans-boundary influences. Elevated urban levels were measured along the southeastern coast and in south-central China; the highest concentration was observed in the city of Kunming (66 pg m(-3)). Few of the urban samples (7%) and a majority of the rural samples (62%) were below the method detection limit, notably areas in rural central and northeastern China. The mean fractional abundance of the syn-DP isomer (f(syn)) in all samples was 0.33 +/- 0.10, values indistinguishable from that of a commercial mixture (f(syn) = 0.35). This paper represents the first report on DP levels in Chinese air, together with isomeric ratio profiles from urban and rural sites.

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 score0.023
Threshold uncertainty score0.046

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 communication0.0000.000
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 head0.007
GPT teacher head0.223
Teacher spread0.216 · 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

Citations169
Published2008
Admission routes1
Has abstractyes

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Same venueEnvironmental Science & TechnologySame topicToxic Organic Pollutants ImpactFrench-language works237,207