MétaCan
Menu
Back to cohort
Record W2083096911 · doi:10.1002/etc.1932

Understanding the atmospheric measurement and behavior of perfluorooctanoic acid

2012· article· en· W2083096911 on OpenAlexaff
Eva Webster, David Ellis

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsTrent University
Fundersnot available
KeywordsPerfluorooctanoic acidPartition coefficientChemistryEnvironmental chemistryPassive samplingCorrelation coefficientParticle (ecology)Gas phaseArtifact (error)Sampling (signal processing)Partition (number theory)Analytical Chemistry (journal)ChromatographyPhysical chemistryStatisticsMathematicsPhysics

Abstract

fetched live from OpenAlex

The recently reported quantification of the atmospheric sampling artifact for perfluorooctanoic acid (PFOA) was applied to existing gas and particle concentration measurements. Specifically, gas phase concentrations were increased by a factor of 3.5 and particle-bound concentrations by a factor of 0.1. The correlation constants in two particle-gas partition coefficient (K(QA)) estimation equations were determined for multiple studies with and without correcting for the sampling artifact. Correction for the sampling artifact gave correlation constants with improved agreement to those reported for other neutral organic contaminants, thus supporting the application of the suggested correction factors for perfluorinated carboxylic acids. Applying the corrected correlation constant to a recent multimedia modeling study improved model agreement with corrected, reported, atmospheric concentrations. This work confirms that there is sufficient partitioning to the gas phase to support the long-range atmospheric transport of PFOA.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.047
GPT teacher head0.242
Teacher spread0.195 · 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

Citations7
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueEnvironmental Toxicology and ChemistrySame topicPer- and polyfluoroalkyl substances researchFrench-language works237,207