Evidence map›Paper›PMID 38095508›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024

Data-Driven Compound Identification in Atmospheric Mass Spectrometry.

Hilda Sandström, Matti Rissanen, Juho Rousu, Patrick Rinke

Open access · goldAbstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Data-Driven Compound Identification in Atmospheric Mass Spectrometry.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Hilda SandströmDepartment of Applied Physics, Aalto University, P.O. Box 11000, FI-00076, Aalto, Espoo, Finland.
Matti RissanenAerosol Physics Laboratory, Tampere University, FI-33720, Tampere, Finland.
Juho RousuDepartment of Computer Science, Aalto University, P.O. Box 11000, FI-00076, Aalto, Espoo, Finland.
Patrick RinkeDepartment of Applied Physics, Aalto University, P.O. Box 11000, FI-00076, Aalto, Espoo, Finland.ORCID https://orcid.org/0000-0003-1898-723X
Aalto University · FIUniversity of Helsinki · FI

Funding

HORIZON EUROPE European Research Council 101002728Research Council of Finland 334790Research Council of Finland 339421Research Council of Finland 345802Research Council of Finland 346373Research Council of Finland 346377Research Council of Finland 353836Research Council of Finland 358066
6 · The paper itself

Abstract

Aerosol particles found in the atmosphere affect the climate and worsen air quality. To mitigate these adverse impacts, aerosol particle formation and aerosol chemistry in the atmosphere need to be better mapped out and understood. Currently, mass spectrometry is the single most important analytical technique in atmospheric chemistry and is used to track and identify compounds and processes. Large amounts of data are collected in each measurement of current time-of-flight and orbitrap mass spectrometers using modern rapid data acquisition practices. However, compound identification remains a major bottleneck during data analysis due to lacking reference libraries and analysis tools. Data-driven compound identification approaches could alleviate the problem, yet remain rare to non-existent in atmospheric science. In this perspective, the authors review the current state of data-driven compound identification with mass spectrometry in atmospheric science and discuss current challenges and possible future steps toward a digital era for atmospheric mass spectrometry.

Indexed as

aerosoldatabasemachine learningmass spectrometryopen science

Identifiers

PMID38095508
PMCPMC10885664
OpenAlexW4389732247

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.