Evidence map›Paper›PMID 36211001›Full record

ArticleComputational intelligence and neuroscience2022

Practical Research on Artificial Intelligence Algorithms, Paleontology, Data Mining, and Digital Restoration of Public Information.

Guo Yan, Hong Xin

RetractedAbstract readRetracted Publication
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Guo YanDigital Protection and Application of Paleontology Lab, Media and Animation College, Lu Xun Academy of Fine Arts, Dalian, China.
Hong XinDigital Protection and Application of Paleontology Lab, Media and Animation College, Lu Xun Academy of Fine Arts, Dalian, China.ORCID https://orcid.org/0000-0003-1557-9273

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper discusses the method of fossil digitization combining paleontology and art by using data mining. The aim of the study is to increase the creativity and vitality of museum exhibits and promote scientific exchange. The purpose of the study is to discuss how the interdisciplinary approach will benefit the communication of science and to realize the cooperative development of creative science popularization, art science popularization, dialogue science popularization, and communication science popularization through the cooperation between museums and institutions disseminating and researching science. The research method takes the Jehol Biota in western Liaoning Province of China as an example to explore the methods and approaches to transform museum resources into creative products. Through artificial intelligence data mining and digital reconstruction, data can be used for archaeological research but also for scientific popularization and scientific dissemination of the resources of art transformation. Research results: as the cornerstone to consolidate the digital development of society and economy, "the new infrastructure of artificial intelligence" will start a comprehensive digital transformation. Through the integration of multiple fields and disciplines, museums will change from resource dependence to focus more on market creation, which will promote museum's industry development.

Indexed as

Artificial IntelligencePaleontologyCommunicationData MiningMuseums

Identifiers

PMID36211001
PMCPMC9534629

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.