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Record W3000943008 · doi:10.1002/essoar.10501148.1

How frequent is new particle formation over the remote temperate/boreal forest?

2019· preprint· en· W3000943008 on OpenAlexaboutno aff
Meinrat O. Andreae, T. W. Andreae, Florian Ditas

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsnot available
Fundersnot available
KeywordsTemperate climateTaigaBorealTemperate forestEnvironmental scienceTemperate rainforestAerosolAtmospheric sciencesLatitudePhysical geographyGeographyClimatologyEcologyGeologyForestryMeteorologyEcosystemArchaeology

Abstract

fetched live from OpenAlex

The frequency and intensity of new particle formation (NPF) over remote forest regions in the temperate and boreal zones, and thus the importance of NPF for the aerosol budget and life cycle in the pristine atmosphere, remains controversial. Whereas NPF has been shown to occur relatively frequently at several sites in Scandinavia [1], it was found to be nearly absent at a mid-continental site in Siberia [2]. To explore this issue further, we made measurements of aerosol size distributions between 10 and 300 nm diameter at two remote sites in the transition region between temperate and boreal forest in British Columbia, Canada. The measurements covered 23 days during the month of June 2019, at the time when NPF typically reaches its seasonal maximum in remote mid-latitude regions. These are the first such measurements on the North American continent. Although the sites were only 150 km apart, there were dramatic differences in NPF frequency and intensity between them. At the Eagle Lake site, NPF occurred almost daily and nucleation mode particle concentrations reached above 5000 cm-3. In contrast, at the Nazko River site, there were only 6 NPF events in 11 days and nucleation mode particle concentrations reached only about 800 cm-3. The reasons for this difference are under investigation. They may include airmass origins, pre-existing aerosols, density of forest cover in the surrounding regions, and proximity to the Pacific coast. Our results suggest that measurement campaigns in the remote forest regions of North America to investigate the role of NPF with a more comprehensive set of instrumentation are essential for a deeper scientific understanding of this important process. [1] Nieminen et al., Atmos. Chem. Phys. 18 (2018) 14737-14756. [2] Wiedensohler et al., Atmospheric Environment, 200 (2019) 167-169.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.223
Teacher spread0.199 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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