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Faculty of 1000 - Wikipedia, the free encyclopedia

Faculty of 1000

From Wikipedia, the free encyclopedia

Faculty of 1000 is a website for scientists that provides rankings and commentary on current scientific research papers. The service is designed to act as a filter, highlighting the most significant research along with evaluations of the research written by other scientists that emphasize why a particular research paper is interesting or important.

Faculty of 1000 currently exists as two sister sites:

Faculty of 1000 Biology is an online awareness service for biologists. It is produced by a panel of over 2000 biological researchers, who regularly identify and evaluate the research articles that they have found most interesting in the recently published literature.

Faculty of 1000 Medicine is a similar literature evaluation and awareness service for medicine. Based on the recommendations of a selected faculty of more than 2500 international researchers and clinicians, it systematically highlights and reviews the most pertinent papers in any field of medicine. The aim of F1000 Medicine is to eliminate what can be seen as existing bias within the medical community with regards to articles being rated according to the prestige of the journal in which they are published Impact factor) and not on the actual merit of the article,

A feature of the site is the Hidden Jewels page, which identifies articles that have been highly rated by scientists, but which were not published in one of the dozen or so most highly read journals, and so may have been missed.

Faculty of 1000 is a web based service which runs on the same principle as other large web based data services - known collectively as web 2.0 systems. It is the contributors which 'build' these sites through their collective input.

Members evaluate using a tagging system, in the process giving their own opinions, in other words they are peer reviewed (this system of peer review through classification is known as a Folksonomy). This complements current quantitative approaches to evidence-based medicine.

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