suggestions for better papers what the judges look for in a paper why judges reject papers
TRANSCRIPT
Suggestions for better papers
• What the judges look for in a paper
• Why judges reject papers
Suggestions for better papers
What the judges look for in a paper:
1.Objectives that are clearly stated in the introduction
2. Concise methods that are logical and free from jargon
3.Results that relate to the objectives
4.Conclusions that are justified by the results
Organization
• Introduction
• Materials and methods
• Results
• Discussion
• Conclusion
Introduction
• Include some background
• State your objectives
• Explain why the research is important
• If your research is similar to something published, explain how your work is different
• We often reject papers that are “copies” of published work
Materials and Methods
• Should be a logical description of what you did
• Make sure that a lay person would understand your methods
• Explain how your methods will allow you to meet your objectives
• Do not list materials used in your project
Results
• The most important section of your paper (and your presentation)
• Should be easy to interpret by all judges
• Emphasize the important points of your results (don’t make us guess)
Results: Figures
• Usually better than tables
• Make sure that figures can stand alone
• Make sure that the figures clearly indicate something important
• Each figure should be referenced in the text of your results
Discussion and Conclusion
• Should relate to the objectives stated in the introduction
• Should be clearly tied to your results and should not go beyond your data
Why judges reject papers
• Literature searches
• Work that is a repeat of something published and does not expand beyond the original work
• Poor study design
• If we cannot interpret your results
• If we do not understand what the figures are supposed to indicate
Problems in Study Design
• Sample size insufficient to indicate a trend
• Samples insufficiently distributed on the x-axis
• Samples should usually be randomly drawn and independent of one another
Not enough data to indicate a trend
1011121314151617181920
10 15 20 25
Sample insufficiently distributed on the x-axis
1011121314151617181920
10 15 20 25
r2=0.78, F1,4=6.07, P=0.032
Balanced Linear Regression
0.0
3.0
6.0
9.0
12.0
0.0 2.5 5.0 7.5 10.0
y_axis vs x_axis
x_axis
y_axi
s
r2=0.89, F1,38=389, P=0.000
Sample insufficient across the x-axis
4.5
5.5
6.5
7.5
8.5
6.0 6.5 7.0 7.5 8.0
y_axis vs x_axis
x_axis
y_axi
s
r2=0.01, F1,38=.07, P=0.841
Independent Samples?
When are non-independent samples are OK?
• Multiple measurements on an individual to track a response
• Before and after measurements on subjects
• Can be dealt with statistically (repeated measures ANOVA or paired t-tests)
Statistical outliers
• What do we do with outliers?
• Do nothing when you can’t justify deleting
• In regression, conduct “robust regression”
• Delete if you can justify
Examples from previous speakers
• To illustrate some common problems
Figure 1 Density of Epidermal Nerve Fibers (# nerve branches per Millimeter of epidermal border length + Standard Error)
0
2
4
6
8
10
12
14
16
18
Control Pre-Diabetic Diabetic
Avera
ge N
erv
e C
ount
Control
Pre-Diabetic
Diabetic
Figure 1 Density of Epidermal Nerve Fibers (# nerve branches per Millimeter of epidermal border length + Standard Error)
0
2
4
6
8
10
12
14
16
18
Control Pre-Diabetic Diabetic
Avera
ge N
erv
e C
ount
Rule 2: Avoid Jargon and be careful with abbreviations
DIFFERENTIALLY EXPRESSED GENES IDENTIFIED BY SAM
Positive Differentially Expressed Genes, 173
Non- Significant Genes, 6647
Negative Differentially Expressed Genes, 11
Positive Differentially Expressed Genes Negative Differentially Expressed Genes Non- Significant Genes
(pos 173) (neg 11) (neu. 6647)
0
2.5
5
7.5
10
12.5
15
17.5
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58
Genotypes
Tot
al p
olyp
heno
l (g
/100
g dr
y w
eigh
t)
0
0.5
1
1.5
2
2.5
Rad
ical
Sca
veng
ing
activ
ity
(m
ole
Tro
lox/
mg
dry
wei
ght)
Total PolyphenolRadical Scavenging Activity
Radical scavenging activity (µ mole Trolox/mg dry leaf powder) and total polyphenol (g/100 g dry leaf powder) in the leaves of 60 sweetpotato genotypes
High polyphenol accumulators
Medium polyphenol accumulator Low pp accumulatorsLow PP
accumulators
Linear correlations between the total polyphenol contents (g/100g dry matter) and radical scavenging activities (RSA;
mol Trolox/g DM) of sweet potato leaves
y = 0.1303x - 0.2843r = 0.85 (n= 30)
0.3
0.7
1.1
1.5
1.9
2.3
8.0 10.0 12.0 14.0 16.0 18.0Total Polyphenol
RSA
A
B
C
D
Photomicrographs A and B show crystals produced by 500 µM melamine and 500 µM cyanuric acid in H20 (sample 11), at 400X magnification and 40X magnification, respectively. Photomicrographs C and D show crystals
produced by 500 µM melamine and 500 µM cyanuric acid in artificial urine (Sample 6), at 400X magnification and 40X magnification, respectively.
Trial #3 Samples
Solution Weight (in grams) Visible Pellet
Pellet Weight (in grams)
1 0.8460 No n/d
2 0.6832 No n/d
3 1.0030 No 0.0021
4 0.9370 No 0.0033
5 1.0130 No 0.0029
6 0.8990 Yes 0.0136
7 0.9972 No 0.0100
8 0.8131 No 0.0001
9 0.7569 No 0.0055
10 1.0275 No 0.0010
11 1.0025 Yes 0.0016
Pellet weights for Trial 3 samples
•