No it isn't [1].
The best definition I know is
> The P value is defined as the probability, under the assumption of no effect or no difference (the null hypothesis), of obtaining a result equal to or more extreme than what was actually observed.
S. N. Goodman. Toward evidence-based medical statistics. 1: The P value fallacy. Annals of Internal Medicine, 130:995–1004, 1999.
edit: oh dear, and then the Ars article says "Individual experiments may be wrong five percent of the time," but that's exactly what p values do not measure. Statistics is hard.
For the purposes of understanding the definition, another way of looking at it is basically a 'statistical proof by contradiction':
1. Assume null hypothesis is true
2. Compute test statistic
3. Ask the question, "What is the probability of obtaining that test statistic or one more extreme?" (this probability is the p-value)
4. Pick a threshold (usually 0.05 but this is totally arbitrary)
5. If p < threshold then conclude the null hypothesis is false and reject it.
Reductio ad statistico absurdum.