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Record W2543450213 · doi:10.1186/s40645-016-0109-2

A review of atmospheric chemistry observations at mountain sites

2016· review· en· W2543450213 on OpenAlexfundno aff
Sachiko Okamoto, Hiroshi Tanimoto

Bibliographic record

VenueProgress in Earth and Planetary Science · 2016
Typereview
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsnot available
FundersArmy Research OfficeUniversità degli Studi di Urbino Carlo BoEnvironment and Climate Change CanadaNational Oceanic and Atmospheric AdministrationEnvironmental Protection Administration, Executive Yuan, R.O.C. TaiwanPaul Scherrer InstitutChina Meteorological AdministrationUniversity of WashingtonNational Central UniversityTokyo Metropolitan UniversityU.S. Environmental Protection Agency
KeywordsEnvironmental scienceTrace gasTropospheric ozoneAtmospheric chemistryTroposphereAtmospheric sciencesAltitude (triangle)Reactive nitrogenBiomass burningOzoneAerosolMeteorologyGeologyNitrogenChemistryGeography

Abstract

fetched live from OpenAlex

Located far from anthropogenic emission sources, high-altitude mountain stations are considered to be ideal sites for monitoring climatic and environmentally important baseline changes in free tropospheric trace gases and aerosols. In addition, the observations taken at these stations are often used to study the long-range transport of dust as well as anthropogenic and biomass burning pollutants from source regions and to evaluate the performance of global and regional models. In this paper, we summarize the results from past and ongoing field measurements of atmospheric constituents at high-altitude stations across the globe, with particular emphasis on reactive trace species including tropospheric ozone, along with its precursors such as carbon monoxide, nitrogen oxides, total reactive nitrogen, and nonmethane hydrocarbons. Over the past decades, our understanding of the temporal variability and meteorological mechanisms of long-range transport has advanced in tandem with progress in instrumentation and modeling. Finally, the future needs of atmospheric chemistry observations at mountain sites are addressed.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.032
GPT teacher head0.271
Teacher spread0.239 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations61
Published2016
Admission routes1
Has abstractyes

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