The Wolf-Rayet stars in the Large Magellanic Cloud

Multilingual Wikipedia

In June 2020 the work The Wolf-Rayet stars in the Large Magellanic Cloud was on the 10,269th 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 427th place in June 2020. From Wikipedians' point of view, "The Wolf-Rayet stars in the Large Magellanic Cloud" is the 3,253rd most reliable publication with DOI number in different language versions of Wikipedia (AR-score).

PR-score:
10,269th place
147,179
-23,951
AR-score:
3,253rd place
18,518
+117
F-score:
427th place
226
+2

English Wikipedia (en)

PR-score:
9,921st place
112,487
-11,374
AR-score:
5,190th place
10,110
+34
F-score:
1,002nd place
51
0

Spanish Wikipedia (es)

PR-score:
12,562nd place
9,929
-5,411
AR-score:
10,658th place
726
+1
F-score:
23,827th place
1
0

Japanese Wikipedia (ja)

PR-score:
8,613th place
8,709
-624
AR-score:
8,080th place
427
+26
F-score:
287th place
24
0

Polish Wikipedia (pl)

PR-score:
10,341st place
3,618
-975
AR-score:
6,029th place
653
0
F-score:
2,041st place
7
0

Russian Wikipedia (ru)

PR-score:
19,681st place
2,877
-431
AR-score:
8,949th place
562
0
F-score:
676th place
16
0

Chinese Wikipedia (zh)

PR-score:
17,481st place
2,595
-970
AR-score:
3,849th place
711
0
F-score:
296th place
18
0

Vietnamese Wikipedia (vi)

PR-score:
8,934th place
860
-817
AR-score:
1,226th place
702
0
F-score:
110th place
23
0

Korean Wikipedia (ko)

PR-score:
10,329th place
715
-564
AR-score:
767th place
1,104
0
F-score:
116th place
21
0

French Wikipedia (fr)

PR-score:
52,358th place
330
-838
AR-score:
7,716th place
997
0
F-score:
3,937th place
6
0

Arabic Wikipedia (ar)

PR-score:
34,316th place
294
-285
AR-score:
2,492nd place
978
+20
F-score:
339th place
14
0
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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...