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Bacterial Wall as Target for Attack: Past, Present, and Future Research

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Multilingual Wikipedia

In June 2020 the work Bacterial Wall as Target for Attack: Past, Present, and Future Research was on the 22,852nd 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 13,661st place in June 2020. From Wikipedians' point of view, "Bacterial Wall as Target for Attack: Past, Present, and Future Research" is the 8,157th most reliable publication with DOI number in different language versions of Wikipedia (AR-score).

PR-score:
22,852nd place
90,892
-41,056
AR-score:
8,157th place
11,551
-446
F-score:
13,661st place
28
0

English Wikipedia (en)

PR-score:
37,065th place
49,709
-13,542
AR-score:
15,322nd place
5,781
+1
F-score:
84,123rd place
4
0

Chinese Wikipedia (zh)

PR-score:
5,708th place
8,770
-4,563
AR-score:
4,947th place
592
0
F-score:
10,008th place
2
0

Portuguese Wikipedia (pt)

PR-score:
5,455th place
6,804
-7,416
AR-score:
4,856th place
664
-449
F-score:
6,535th place
2
0

Turkish Wikipedia (tr)

PR-score:
757th place
5,483
-1,973
AR-score:
1,606th place
352
0
F-score:
1,432nd place
2
0

Simple English Wikipedia (simple)

PR-score:
248th place
4,900
-3,466
AR-score:
149th place
3,000
0
F-score:
490th place
2
0

Arabic Wikipedia (ar)

PR-score:
3,687th place
3,913
-366
AR-score:
16,493rd place
218
0
F-score:
8,481st place
2
0

Lithuanian Wikipedia (lt)

PR-score:
90th place
1,859
-3,015
AR-score:
237th place
211
0
F-score:
98th place
2
0

Catalan Wikipedia (ca)

PR-score:
1,788th place
1,265
-904
AR-score:
15,360th place
93
+1
F-score:
3,725th place
2
0

Khmer Wikipedia (km)

PR-score:
168th place
40
-10
AR-score:
64th place
13
0
F-score:
37th place
2
0
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Wikipedia Languages

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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