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Uninterpretable graphs at a scientific conference

Faulkes, Z.

2024-11-14 scientific communication and education
10.1101/2024.11.08.622642 bioRxiv
Show abstract

Comparing averages requires knowing sample variation, which can be shown visually using a bar graph with error bars or a box plot. Because error bars and box plots can show different measures, they must be labelled to be interpretable. Of graphs of averages shown at a scientific conference in 2020, 87.5% of graphs did not contain enough information on the slide to interpret them. The only graphs that were fully interpretable (12.5%) were bar graphs. By comparison, 92% of graphs of averages published in a journal in the same field contained enough information to interpret them. While conferences are not and should not be as stringent about data presentation as journals, that a statistical value as simple as an average are not clearly presented suggests graphs are created by rote.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
Ecology and Evolution
○ 267 papers in training set
Top 0.1%
18.8%
Similar papers in this journal
2
PLOS ONE
● 5266 papers in training set
Top 12%
15.3%
Similar papers in this journal
3
Behavior Research Methods
○ 30 papers in training set
Top 0.1%
9.1%
Similar papers in this journal
4
Royal Society Open Science
● 214 papers in training set
Top 0.3%
6.8%
Similar papers in this journal
50% of probability mass above
5
PeerJ
◐ 308 papers in training set
Top 1%
4.9%
Similar papers in this journal
6
PLOS Biology
● 486 papers in training set
Top 0.8%
4.4%
7
eLife
● 5828 papers in training set
Top 30%
4.1%
8
Ecosphere
○ 57 papers in training set
Top 0.4%
3.3%
9
eneuro
● 439 papers in training set
Top 3%
2.7%
10
Ecological Informatics
○ 33 papers in training set
Top 0.3%
2.2%
11
Wellcome Open Research
○ 67 papers in training set
Top 0.3%
2.2%
12
F1000Research
○ 88 papers in training set
Top 1%
1.9%
13
Proceedings of the Royal Society B: Biological Sciences
● 393 papers in training set
Top 3%
1.9%
14
Heliyon
○ 152 papers in training set
Top 3%
1.8%
15
Animals
○ 23 papers in training set
Top 0.4%
1.8%
16
Frontiers in Veterinary Science
○ 32 papers in training set
Top 0.3%
1.7%
17
Frontiers in Integrative Neuroscience
○ 15 papers in training set
Top 0.1%
1.4%
18
Frontiers in Marine Science
○ 62 papers in training set
Top 0.8%
1.1%
19
Frontiers in Bioinformatics
○ 49 papers in training set
Top 1%
1.0%
20
Journal of Cognitive Neuroscience
● 135 papers in training set
Top 2%
0.9%
21
Scientific Reports
○ 3612 papers in training set
Top 70%
0.9%
22
Behavioral Ecology
◐ 36 papers in training set
Top 0.6%
0.9%
23
Conservation Biology
○ 17 papers in training set
Top 0.3%
0.9%
24
Frontiers in Psychiatry
○ 87 papers in training set
Top 2%
0.9%
25
Biology
○ 45 papers in training set
Top 0.8%
0.9%
26
Frontiers in Psychology
○ 56 papers in training set
Top 1%
0.9%
27
American Journal of Primatology
○ 20 papers in training set
Top 0.3%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.