Evidence map›Paper›PMID 39030317›Full record

ArticleScientific reports2024

Absolute permeability estimation from microtomography rock images through deep learning super-resolution and adversarial fine tuning.

Júlio de Castro Vargas Fernandes, Alyne Duarte Vidal, Lizianne Carvalho Medeiros, Carlos Eduardo Menezes Dos Anjos, Rodrigo Surmas, Alexandre Gonçalves Evsukoff

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 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
–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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Júlio de Castro Vargas FernandesCOPPE-Federal University of Rio de Janeiro, Mailbox 68506, Rio de Janeiro, Rio de Janeiro, 21941-972, Brazil. juliocvf@poli.ufrj.br.
Alyne Duarte VidalCOPPE-Federal University of Rio de Janeiro, Mailbox 68506, Rio de Janeiro, Rio de Janeiro, 21941-972, Brazil.
Lizianne Carvalho MedeirosCOPPE-Federal University of Rio de Janeiro, Mailbox 68506, Rio de Janeiro, Rio de Janeiro, 21941-972, Brazil.
Carlos Eduardo Menezes Dos AnjosCOPPE-Federal University of Rio de Janeiro, Mailbox 68506, Rio de Janeiro, Rio de Janeiro, 21941-972, Brazil.
Rodrigo SurmasCENPES-Petrobras, Av. Horácio Macedo, 950, Rio de Janeiro, Rio de Janeiro, 21941-915, Brazil.
Alexandre Gonçalves EvsukoffCOPPE-Federal University of Rio de Janeiro, Mailbox 68506, Rio de Janeiro, Rio de Janeiro, 21941-972, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The carbon capture and storage (CCS) process has become one of the main technologies used for mitigating greenhouse gas emissions. The success of CCS projects relies on accurate subsurface reservoir petrophysical characterization, enabling efficient storage and captured

Identifiers

PMID39030317
PMCPMC11271552

What OpenQuestion holds

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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.