Evidence map›Paper›PMID 39939386›Full record

ArticleScientific reports2025

Application of machine learning approach to estimate the solubility of some solid drugs in supercritical CO

Zahra Bahrami, Fatemeh Bashipour, Alireza Baghban

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

3 authors.

Zahra BahramiFaculty of Petroleum and Chemical Engineering, Razi University, Kermanshah, 67149-67346, Iran.
Fatemeh BashipourFaculty of Petroleum and Chemical Engineering, Razi University, Kermanshah, 67149-67346, Iran. f.bashipour@razi.ac.ir.
Alireza BaghbanProcess engineering department, National Iranian South Oilfields Company (NISOC), Ahvaz, Iran. alireza_baghban@alumni.ut.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate estimation of the solubility of solid drugs (SDs) in the supercritical carbon dioxide (SC-CO

Indexed as

Carbon DioxideMachine LearningFuzzy LogicPharmaceutical PreparationsSolubilityCarbon DioxidePharmaceutical PreparationsANFISArtificial intelligence modelingGEPSolid drugsSolubilitySupercritical CO2

Identifiers

PMID39939386
PMCPMC11822099

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.