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Record W2017459392 · doi:10.1021/es502081j

Temporal Variations of Cyclic and Linear Volatile Methylsiloxanes in the Atmosphere Using Passive Samplers and High-Volume Air Samplers

2014· article· en· W2017459392 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironmental Science & Technology · 2014
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsEnvironment and Climate Change Canada
FundersEnvironment CanadaUnited Nations Environment ProgrammeGovernment of Canada
KeywordsSnowVolume (thermodynamics)Environmental scienceSorbentAtmosphere (unit)Environmental chemistryParticulatesAtmospheric sciencesChemistryMeteorologyGeologyAdsorptionGeography

Abstract

fetched live from OpenAlex

Cyclic and linear volatile methylsiloxanes (cVMSs and lVMSs, respectively) were measured in ambient air over a period of over one year in Toronto, Canada. Air samples were collected using passive air samplers (PAS) consisting of sorbent-impregnated polyurethane foam (SIP) disks in parallel with high volume active air samplers (HV-AAS). The average difference between the SIP-PAS derived concentrations in air for the individual VMSs and those measured using HV-AAS was within a factor of 2. The air concentrations (HV-AAS) ranged 22-351 ng m(-3) and 1.3-15 ng m(-3) for ΣcVMSs (D3, D4, D5, D6) and ΣlVMSs (L3, L4, L5), respectively, with decamethylcyclopentasiloxane (D5) as the dominant compound (∼75% of the ΣVMSs). Air masses arriving from north to northwest (i.e., less populated areas) were significantly less contaminated with VMSs compared to air arriving from the south that are impacted by major urban and industrial areas in Canada and the U.S. (p < 0.05). In addition, air concentrations of ΣcVMSs were lower during major snowfall events (on average, 73 ng m(-3)) in comparison to the other sampling periods (121 ng m(-3)). Ambient temperature had a small influence on the seasonal trend of VMS concentrations in air, except for dodecamethylcyclohexasiloxane (D6), which was positively correlated with the ambient temperature (p < 0.001).

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.524

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.009
GPT teacher head0.224
Teacher spread0.215 · 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