Evidence map›Paper›PMID 34451590›Full record

ArticlePlants (Basel, Switzerland)2021

Raman Spectroscopy and Machine-Learning for Early Detection of Bacterial Canker of Tomato: The Asymptomatic Disease Condition.

Moisés Roberto Vallejo-Pérez, Jesús Antonio Sosa-Herrera, Hugo Ricardo Navarro-Contreras, Luz Gabriela Álvarez-Preciado, Ángel Gabriel Rodríguez-Vázquez, José Pablo Lara-Ávila

Open access · goldAbstract read
In one paragraph

Article in Plants (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.9field-weighted citation impact, top 16% 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

11 citing papers in PubMed, 30 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Moisés Roberto Vallejo-PérezConsejo Nacional de Ciencia y Tecnología-Universidad Autónoma de San Luis Potosí, CIACYT, Alvaro Obregon 64, Col. Centro, San Luis Potosí 78000, Mexico.ORCID 0000-0002-9167-2632
Jesús Antonio Sosa-HerreraConsejo Nacional de Ciencia y Tecnología-Centro de Investigación en Ciencias de Información Geoespacial A. C., Laboratorio Nacional de Geointeligencia, Aguascalientes 20313, Mexico.
Hugo Ricardo Navarro-ContrerasCoordinación para la Innovación y la Aplicación de la Ciencia y la Tecnología (CIACYT), Universidad Autónoma de San Luis Potosí, Av. Sierra Leona 550, Col Lomas 2a. Sección, San Luis Potosí 78210, Mexico.
Luz Gabriela Álvarez-PreciadoCoordinación para la Innovación y la Aplicación de la Ciencia y la Tecnología (CIACYT), Universidad Autónoma de San Luis Potosí, Av. Sierra Leona 550, Col Lomas 2a. Sección, San Luis Potosí 78210, Mexico.
Ángel Gabriel Rodríguez-VázquezCoordinación para la Innovación y la Aplicación de la Ciencia y la Tecnología (CIACYT), Universidad Autónoma de San Luis Potosí, Av. Sierra Leona 550, Col Lomas 2a. Sección, San Luis Potosí 78210, Mexico.
José Pablo Lara-ÁvilaFacultad de Agronomía y Veterinaria, Universidad Autónoma de San Luis Potosí, Km. 14.5 Carretera San Luis Potosí, Matehuala, Ejido Palma de la Cruz, Soledad de Graciano Sánchez, San Luis Potosí 78321, Mexico.
Autonomous University of San Luis Potosí · MXSecretaría de Ciencia, Humanidades, Tecnología e Innovación · MX

Funding

Consejo Nacional de Ciencia y Tecnología Catedras CONACYT 2210, 2643
6 · The paper itself

Abstract

Bacterial canker of tomato is caused by

Indexed as

Clavibacter michiganensis subsp. michiganensislinear discriminant analysis (LDA)multilayer perceptron (MLP)plant disease surveillanceprecision farmingprincipal component analysis (PCA)

Identifiers

PMID34451590
PMCPMC8399098
OpenAlexW3183985553

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.