One way to get to the goal is to introduce a scale of values and assign values from 1 to 10.
This we need to define the level of knowledge and relevance achieved with a certain type of research: with a factor of 1, more than "I found" we are facing "maybe it could even be if ..."; a factor 10 instead leads to the mathematical certainty that a given event is exactly as described by the study.
A research that has a factor of 1 could be the beginning of a new line of research, a beginning to see if, how and when, something actually happens; a type of research that reaches 10, changes the guidelines.
It must be emphasized that I am speaking of different types of publications, not of single works: for this reason the value will never be exactly defined but it can vary for that type of publication. Of course there are many jobs that come within a factor of 1, but 10 is practically a chimera: science goes on for verification and the idea that there is a type of study that can change the world by itself is very unlikely.
In this context, this scale only serves to understand how to classify what we find on PubMed, and that is often reported in the articles: can I rely more on a single study or a cohort study? Is a clinical trial or a case-control study more relevant?
There is in literature what is called evidence pyramid, the scale that I will use in this article is inspired by the new version of this pyramid, proposed in 2016.
Value of a scientific study
MAQ/March 2018/56