Atomic structure and chemistry of human serum albumin

Multilingual Wikipedia

In June 2020 the work Atomic structure and chemistry of human serum albumin was on the 2,515th 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 40,561st place in June 2020. From Wikipedians' point of view, "Atomic structure and chemistry of human serum albumin" is the 8,599th most reliable publication with DOI number in different language versions of Wikipedia (AR-score).

PR-score:
2,515th place
316,752
-34,599
AR-score:
8,599th place
11,232
+37
F-score:
40,561st place
14
0

English Wikipedia (en)

PR-score:
4,634th place
169,500
-18,652
AR-score:
27,809th place
4,147
0
F-score:
156,695th place
3
0

Chinese Wikipedia (zh)

PR-score:
222nd place
84,250
+900
AR-score:
1,143rd place
1,600
0
F-score:
33,866th place
1
0

Persian Wikipedia (fa)

PR-score:
51st place
32,100
-1,200
AR-score:
332nd place
1,400
0
F-score:
7,811th place
1
0

Swedish Wikipedia (sv)

PR-score:
114th place
18,400
-12,350
AR-score:
533rd place
1,475
0
F-score:
4,781st place
1
0

Vietnamese Wikipedia (vi)

PR-score:
916th place
7,859
-2,581
AR-score:
16,706th place
60
0
F-score:
26,609th place
1
0

Arabic Wikipedia (ar)

PR-score:
5,227th place
2,881
-100
AR-score:
9,506th place
381
0
F-score:
28,418th place
1
0

Hindi Wikipedia (hi)

PR-score:
219th place
1,350
-37
AR-score:
135th place
825
+38
F-score:
427th place
3
0

Tamil Wikipedia (ta)

PR-score:
1,613th place
250
-300
AR-score:
78th place
1,200
0
F-score:
3,212th place
1
0

Scots Wikipedia (sco)

PR-score:
849th place
133
-133
AR-score:
873rd place
33
0
F-score:
1,266th place
1
0

Galician Wikipedia (gl)

PR-score:
13,671st place
27
-145
AR-score:
2,638th place
110
0
F-score:
9,004th place
1
0

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...