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The species Severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2

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Multilingual Wikipedia

In June 2020 the work The species Severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2 was on the 730th place in the ranking of the most reliable and popular publications with DOI number in multilingual Wikipedia from readers' point of view (PR-score). If we consider only frequency of appearance of this source in references of Wikipedia articles (F-score), this work was on the 2,180th place in June 2020. From Wikipedians' point of view, "The species Severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2" is the 9,410th most reliable publication with DOI number in different language versions of Wikipedia (AR-score).

PR-score:
730th place
588,912
-595,434
AR-score:
9,410th place
10,712
-25
F-score:
2,180th place
82
0

English Wikipedia (en)

PR-score:
1,247th place
324,752
-335,751
AR-score:
23,737th place
4,545
-247
F-score:
31,131st place
8
0

Italian Wikipedia (it)

PR-score:
127th place
81,400
-92,380
AR-score:
2,890th place
1,200
+100
F-score:
3,822nd place
4
0

Czech Wikipedia (cs)

PR-score:
35th place
80,258
-77,697
AR-score:
190th place
2,236
+6
F-score:
303rd place
7
0

Portuguese Wikipedia (pt)

PR-score:
776th place
32,310
-20,364
AR-score:
14,617th place
207
+20
F-score:
3,643rd place
4
0

Chinese Wikipedia (zh)

PR-score:
1,554th place
25,508
-29,634
AR-score:
2,239th place
1,046
+60
F-score:
1,411th place
8
0

Vietnamese Wikipedia (vi)

PR-score:
401st place
13,660
-19,211
AR-score:
3,807th place
303
+7
F-score:
1,911th place
5
0

Persian Wikipedia (fa)

PR-score:
1,389th place
3,395
-2,345
AR-score:
2,548th place
329
-1
F-score:
1,399th place
3
0

Galician Wikipedia (gl)

PR-score:
251st place
717
-291
AR-score:
9,996th place
34
0
F-score:
320th place
8
0
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About the project

BestRef shows popularity and reliability scores for sources in references of Wikipedia articles in different languages. Data extraction based on complex method using Wikimedia dumps. To find the most popular and reliable sources we used information about over 200 million references of Wikipedia articles. More details...

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