Evidence map›Paper›PMID 35688825›Full record

ArticleScientific reports2022

A photosynthetic rate prediction model using improved RBF neural network.

Liuru Pu, Yuanfang Li, Pan Gao, Haihui Zhang, Jin Hu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

4 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Modeling the COScientific reports · 2023
    Article
  3. Article
  4. 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

5 authors at 1 institution in 1 country.

Liuru PuCollege of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, 712100, Shaanxi, China.
Yuanfang LiCollege of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, 712100, Shaanxi, China.
Pan GaoCollege of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, 712100, Shaanxi, China.
Haihui ZhangCollege of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, 712100, Shaanxi, China.
Jin HuCollege of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, 712100, Shaanxi, China. jhudalab@163.com.
Northwest A&F University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A photosynthetic prediction rate model is a theoretical basis for light environmental regulation, and the existing photosynthetic rate prediction models are limited by low modeling speed and prediction accuracy. Therefore, this paper analyses effects of light quality on photosynthesis rate, and proposes a method based on Radial basis function (RBF) optimized by Quantum genetic algorithm (QGA) to establish photosynthetic rate prediction model. We selected "golden embryo

Indexed as

Artificial IntelligenceCucumis sativusAlgorithmsNeural Networks, ComputerPhotosynthesis

Identifiers

PMID35688825
PMCPMC9187728
OpenAlexW4281684384

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.