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Record W2016091032 · doi:10.1139/s06-054

Source characterization of ambient fine particles in the Los Angeles basin

2007· article· en· W2016091032 on OpenAlexvenueno aff
Eugene Kim, Philip K. Hopke

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsnot available
FundersCalifornia Air Resources BoardNational Oceanic and Atmospheric AdministrationU.S. Environmental Protection Agency
KeywordsSea saltSulfateEnvironmental scienceParticulatesNitrateEnvironmental chemistryStructural basinAerodynamic diameterGasolineEnvironmental engineeringAerosolHydrology (agriculture)GeographyChemistryGeologyMeteorology

Abstract

fetched live from OpenAlex

Integrated 24 h PM 2.5 (particulate matter ≤2.5 µm in aerodynamic diameter) speciation data collected between 2001 and 2004 at three United States Environmental Protection Agency Speciation Trends Network monitoring sites in the Los Angeles (LA) basin (Simi Valley, downtown LA, and Rubidoux) were analyzed through the application of the positive matrix factorization and seven to nine sources were identified. Secondary particles provided the highest contributions to PM 2.5 concentrations (29%–46% for secondary nitrate and 12%–23% for secondary sulfate). Rubidoux, which is located downwind of the LA metropolitan area, and animal feed lots had the highest secondary nitrate concentration, followed by downtown LA. Secondary sulfate concentrations were consistent among three sites. Gasoline vehicle and diesel emissions contributed 12%–22% and 7%–10%, respectively. In addition, other sources such as airborne soil, sea salt, aged sea salt, wood smoke, and incinerator emissions were identified. Key words: source apportionment, Los Angeles basin, speciation trends network, PM 2.5 .

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score0.107

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.005
GPT teacher head0.165
Teacher spread0.160 · 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

Citations21
Published2007
Admission routes1
Has abstractyes

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