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Record W1988523484 · doi:10.1080/15287390252807966

PRELIMINARY ASSESSMENT OF ATMOSPHERIC METHYLCYCLOPENTADIENYL MANGANESE TRICARBONYL AND PARTICULATE MANGANESE IN SELECTED URBAN SITES

2002· article· en· W1988523484 on OpenAlexaffabout
Christiane Thibault, Greg Kennedy, Lise Gareau, Joseph Zayed

Bibliographic record

VenueJournal of Toxicology and Environmental Health · 2002
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsPolytechnique MontréalUniversité de Montréal
Fundersnot available
KeywordsManganeseGasolineNeutron activation analysisEnvironmental chemistryParticulatesNeutron activationEnvironmental scienceChemistryRadiochemistryOrganic chemistryNeutron

Abstract

fetched live from OpenAlex

Methylcyclopentadienyl manganese tricarbonyl (MMT: C9H7MnO3) is an organometallic additive that has been used since 1976 as an octane enhancer in Canadian unleaded gasoline. Very few studies have determined its atmospheric concentrations and only one study offers recent data on its ambient level. This preliminary study aims to assess atmospheric concentrations of MMT and respirable and total Mn (Mn(R) and Mn(T) in selected sites, at two underground car parks and one gasoline station, related to high levels of automobile traffic. It is also an investigation of the applicability of the current analytical method. In total, 34 air samples were collected using a Gil-Air portable pump during 4 consecutive days and then were analyzed by neutron activation analysis. The concentrations vary between 40 and 104 ng/m3 for Mn(R), 146 and 204 ng/m3 for Mn(T) and 6 and 128 ng/m3 for MMT (including ultrafine particulates, Mn(UF). Of the 12 Mn(R) results, 7 showed concentrations greater than the U.S. EPA reference concentration (RfC = 50 ng/m3). The ratios of Mn(R) to Mn(T) varied from 0.20 to 0.65 with a mean of 0.38. The results for MMT and Mn(UF) raise serious doubts about the specificity of the sampling and chemical analysis methodology proposed by the Occupational Safety and Health Administration (OSHA) for MMT in air.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.041
GPT teacher head0.348
Teacher spread0.307 · 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.

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

Citations12
Published2002
Admission routes2
Has abstractyes

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