Evidence map›Paper›PMID 39525962›Full record

ArticleFrontiers in chemistry2024

Predicting the microalgae lipid profile obtained by supercritical fluid extraction using a machine learning model.

Juan David Rangel Pinto, Jose L Guerrero, Lorena Rivera, María Paula Parada-Pinilla, Mónica P Cala, Gina López, Andrés Fernando González Barrios

Abstract read
In one paragraph

Article in Frontiers in chemistry, 2024. 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.

Juan David Rangel PintoGrupo de Diseño de Productos Y Procesos (GDPP), Department of Chemical and Food Engineering, Universidad de los Andes, Bogotá, Colombia.
Jose L GuerreroMetabolomics Core Facility-MetCore, Vice-Presidency for Research, Universidad de los Andes, Bogotá, Colombia.
Lorena RiveraUnidad de Saneamiento y Biotecnología Ambiental (USBA), Departamento de Biología, Facultad de Ciencias, Pontificia Universidad Javeriana (PUJ), Bogotá, Colombia.
María Paula Parada-PinillaUnidad de Saneamiento y Biotecnología Ambiental (USBA), Departamento de Biología, Facultad de Ciencias, Pontificia Universidad Javeriana (PUJ), Bogotá, Colombia.
Mónica P CalaMetabolomics Core Facility-MetCore, Vice-Presidency for Research, Universidad de los Andes, Bogotá, Colombia.
Gina LópezUnidad de Saneamiento y Biotecnología Ambiental (USBA), Departamento de Biología, Facultad de Ciencias, Pontificia Universidad Javeriana (PUJ), Bogotá, Colombia.
Andrés Fernando González BarriosGrupo de Diseño de Productos Y Procesos (GDPP), Department of Chemical and Food Engineering, Universidad de los Andes, Bogotá, Colombia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study a Machine Learning model was employed to predict the lipid profile from supercritical fluid extraction (SFE) of microalgae

Indexed as

COSMO-SACextremophile microalgaelipidomicregression modelssupercritical fluid extraction

Identifiers

PMID39525962
PMCPMC11543471

What OpenQuestion holds

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LicenceCC BY
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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.