Evidence map›Paper›PMID 38312028›Full record

ArticleScience progress

Special collections for applying artificial intelligence techniques to encourage economic growth and maintain sustainable societies.

Wu Nanping, Tsung-Ju Lee, Li-Jiun Chen, Chih-Chun Kung

Abstract readEditorial
In one paragraph

Article in Science progress. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Wu NanpingInstitute of Deep-Sea Science & Engineering, Chinese Academy of Sciences, Sanya, China.
Tsung-Ju LeeDepartment of Finance, Feng Chia University, Taichung, Taiwan R.O.C.
Li-Jiun ChenDepartment of Finance, Feng Chia University, Taichung, Taiwan R.O.C.
Chih-Chun KungInstitute of Interdisciplinary Research, Shandong University, Weihai, China.ORCID 0000-0003-2951-8711

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Efficient resource use requires substantial evaluation and re-evaluation of production processes. Since not all production details can be properly and timely monitored and adjusted, improvement of resource allocation has long been a critical issue in commodity production, technique selection, and sustainable development. The progress of artificial intelligence (AI) offers a possibility. For example, with deep learning techniques and extensive data analysis, most previously unincorporated or unknown information associated with a firm's activities can be appropriately reflected and calculated. Once the firms take the report, a more efficient and economically friendly production strategy could be made. The central theme of this special collection is to invite studies on how the design and application of AI benefit not only the fields of computer science and information engineering but also the interdisciplinary fields, including renewable energy development, environmental protection, and economic analysis. Fourteen papers are published in this special collection.

Indexed as

Climate changemodel specificationsocial welfaresustainabilitytechnology innovation

Identifiers

PMID38312028
PMCPMC10846185

What OpenQuestion holds

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LicenceCC BY-NC
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.