| 1 | NATURE | 1.74951 |
| 2 | PROC NAT ACAD SCI USA | 1.68111 |
| 3 | SCIENCE | 1.5258 |
| 4 | PHYS REV LETT | 1.26903 |
| 5 | J BIOL CHEM | 1.09737 |
| 6 | J AM CHEM SOC | 0.90221 |
| 7 | PHYS REV B | 0.77051 |
| 8 | APPL PHYS LETT | 0.7182 |
| 9 | CELL | 0.70117 |
| 10 | NEW ENGL J MED | 0.67401 |
| 11 | ANGEW CHEM INT EDIT | 0.5278 |
| 12 | ASTROPHYS J | 0.51421 |
| 13 | J NEUROSCI | 0.48754 |
| 14 | BLOOD | 0.44662 |
| 15 | CIRCULATION | 0.42911 |
| 16 | J IMMUNOL | 0.42728 |
| 17 | CANCER RES | 0.41886 |
| 18 | J PHYS CHEM B | 0.3845 |
| 19 | LANCET | 0.38036 |
| 20 | J CLIN ONCOL | 0.3654 |
| 21 | NUCLEIC ACIDS RES | 0.35345 |
| 22 | J GEOPHYS RES | 0.34899 |
| 23 | PHYS REV D | 0.33641 |
| 24 | NAT GENET | 0.33311 |
| 25 | JAMA-J AM MED ASSOC | 0.33271 |
| 26 | J APPL PHYS | 0.32294 |
| 27 | MOL CELL | 0.30146 |
| 28 | MOL CELL BIOL | 0.29137 |
| 29 | J CHEM PHYS | 0.29136 |
| 30 | ASTRON ASTROPHYS | 0.28497 |
| 31 | MON NOT R ASTRON SOC | 0.28081 |
| 32 | NANO LETT | 0.27487 |
| 33 | GENE DEV | 0.26808 |
| 34 | GEOPHYS RES LETT | 0.26613 |
| 35 | NEURON | 0.26323 |
| 36 | J CLIN INVEST | 0.25632 |
| 37 | EMBO J | 0.24913 |
| 38 | PHYS REV E | 0.24908 |
| 39 | ONCOGENE | 0.24077 |
| 40 | PHYS REV A | 0.23938 |
| 41 | LANGMUIR | 0.23718 |
| 42 | CURR BIOL | 0.23404 |
| 43 | J CELL BIOL | 0.23232 |
| 44 | J EXP MED | 0.23223 |
| 45 | J AM COLL CARDIOL | 0.23015 |
| 46 | J VIROL | 0.22799 |
| 47 | CHEM COMMUN | 0.22567 |
| 48 | CLIN CANCER RES | 0.22319 |
| 49 | BIOCHEMISTRY-US | 0.21736 |
| 50 | J MOL BIOL | 0.21679 |
特徵因子：
Eigenfactor
From Wikipedia, the free encyclopedia
The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. In a manner reminiscent of Google's Pagerank algorithm, journals are rated according to the number of incoming citations, with citations from highly-ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly-ranked journals.[1] As a measure of importance, the Eigenfactor score scales with the size of a journal. All else equal, larger journals have larger Eigenfactor scores. As such, Eigenfactor scores are not directly comparable to impact factor scores, which are a measure of per-article prestige. To allow per-article comparisons using the Eigenfactor approach, the Article Influence score scales Eigenfactor score by the number of articles published by the journal and thus is directly comparable to impact factor.
Eigenfactor scores and Article Influence scores are calculated by eigenfactor.org, where they can be freely viewed. Eigenfactor scores are intended to give a measure of how likely a journal is to be used, and are thought to reflect how frequently an average researcher would access content from that journal.[1]
The Eigenfactor approach is thought to be more robust than the impact factor metric,[2] which purely counts incoming citations without considering the significance of those citations.[3] While the Eigenfactor scores is correlated with total citation count for medical journals,[4] these metrics provide significantly different information.[5]
Eigenfactor scores are measures of a journal's importance and thus should not be used to evaluate individual scientists. To do so would be a mistake because due to the large variance in citation rate and quality of papers within even the most prestigious journals. The H-index is sometimes considered the most robust indicator of a scientist's productivity,[3] but a number of shortcomings of the index have been much-debated and corrected indices proposed.[6]
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