Evidence map›Paper›PMID 41281299›Full record

ArticleAerobiologia2025

Operational pollen classification using digital holography and fluorescence.

Benoît Crouzy, Marie-Pierre Meurville, Bernard Clot, Sophie Erb, Maria Lbadaoui-Darvas, Fiona Tummon, Gian Lieberherr

Abstract read
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In one paragraph

Article in Aerobiologia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Benoît Crouzy *Surface Measurements, MeteoSwiss, Chemin de l'Aérologie, 1530 Payerne, Switzerland.
Marie-Pierre Meurville *Surface Measurements, MeteoSwiss, Chemin de l'Aérologie, 1530 Payerne, Switzerland.
Bernard ClotSurface Measurements, MeteoSwiss, Chemin de l'Aérologie, 1530 Payerne, Switzerland.
Sophie ErbSurface Measurements, MeteoSwiss, Chemin de l'Aérologie, 1530 Payerne, Switzerland.
Maria Lbadaoui-DarvasSurface Measurements, MeteoSwiss, Chemin de l'Aérologie, 1530 Payerne, Switzerland.
Fiona TummonSurface Measurements, MeteoSwiss, Chemin de l'Aérologie, 1530 Payerne, Switzerland.
Gian Lieberherr *Surface Measurements, MeteoSwiss, Chemin de l'Aérologie, 1530 Payerne, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This note introduces the newly developed MeteoSwiss operational pollen classification model based on digital holography and induced fluorescence measurements. A targeted selection of curated training datasets together with a revised model architecture result in considerable improvements compared to previous operational model. The new classification model, which has been trained specifically for Switzerland, is provided openly for use in a standard format for machine learning interoperability. In addition to the description of the new classification model, we motivate the need for this development by presenting the most significant issue met during the first 5 years of operation of the Swiss automatic pollen monitoring network.

Indexed as

Airflow cytometryAutomatic identificationDigital holographyFluorescenceMachine learningPollen monitoringReal-time

Identifiers

PMID41281299
PMCPMC12630167

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.