ArticleHeliyon2022
Improved CRA-method in phenomenological approach (on the example of innovative SME and GHG emissions).
Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Progress in the study of product methodology development and competitiveness assessment model of voluntary carbon offsets.Carbon balance and management · 2026Review
- Impact of Digital Village Construction on Agricultural Carbon Emissions: Evidence from Mainland China.International journal of environmental research and public health · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the successful experience of highly developed countries, for example, in achieving sustainable development, there is no single recipe. Each country can create its own development scenario or combine existing, which will provide it with positive results. We can determine the best ones using the built rating. To build it, the article proposes an approach consisting of several stages. First, the study determines the relationship between the selected factors and the resulting indicator using a correlation analysis. Then, using the Sturges rule, we determine the range and group the countries in the context of each range (group) in accordance with the level of individual indicators. After, we form groups of countries according to the rating. This approach is entirely shown on the impact of small and medium enterprises' innovation on greenhouse gas emissions. Correlation analysis is often used to determine the relationship between factors and resulting indicators. We have shown that its use without additional processing of input data can lead to false results. Therefore, further in the study show imperfection of "blind" correlation and regression analysis in the phenomenological approach. And in our example, offer an improved technique for processing input data for correlation analysis and changed the ranking of countries.
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Registered trials
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.