A Nature tomou medidas para reduzir a falta de reproducibilidade de resultados dos resultados de experiências.
Editorial que explica a iniciativa.
Uma checklist muito interessante a ser preenchida pelos autores. P.ex. diz:
Each figure legend should contain, for each panel where they are relevant:
• the exact sample size (n) for each experimental group/condition, given as a number, not a range;
• a description of the sample collection allowing the reader to understand whether the samples represent technical or biological replicates (including how many animals, litters, cultures, etc.);
• a statement of how many times the experiment shown was replicated in the laboratory;
• definitions of statistical methods and measures:
○ very common tests, such as t-test, simple χ2 tests, Wilcoxon and Mann-Whitney tests, can be unambiguously identified by name only, but more complex techniques should be described in the methods section;
○ are tests one-sided or two-sided?
○ are there adjustments for multiple comparisons?
○ statistical test results, e.g., Pvalues;
○ definition of ‘center values’ as median or average;
○ definition of error bars as s.d. or s.e.m.
Software is not science
Muito interessante, sobre como a ênfase de um trabalho científico não deve ser no software desenvolvido, mas na real contribuição científica do trabalho.
http://matt-welsh.blogspot.pt/2011/11/software-is-not-science.html
http://matt-welsh.blogspot.pt/2011/11/software-is-not-science.html
Publishing a new idea
O nome diz tudo. A "new idea" neste caso era a criptografia de chave pública.
Publishing a new idea
by Ralph C. Merkle
Why Most Published Research Findings Are False
A very interesting paper with devastating conclusions:
Why Most Published Research Findings Are False
John P. A. Ioannidis
PLoS Med, August 2005
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1182327/
Abstract:
There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.
(with thanks to André Falcão)
Why Most Published Research Findings Are False
John P. A. Ioannidis
PLoS Med, August 2005
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1182327/
Abstract:
There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.
(with thanks to André Falcão)
A Style Guide for Students Writing Papers and Reports
A Style Guide for Students Writing Papers and Reports
Gernot Heiser
muito bom
http://www.cse.unsw.edu.au/~gernot/style-guide.html
Gernot Heiser
muito bom
http://www.cse.unsw.edu.au/~gernot/style-guide.html
Research funding: Making the cut
Research funding: Making the cut
Published online 22 September 2010 | Nature 467, 383-385 (2010) | doi:10.1038/467383a
Careers are made and broken by grant-funding committees. So how are the key decisions really made?
Kendall Powell
http://www.nature.com/news/2010/100922/full/467383a.html
Published online 22 September 2010 | Nature 467, 383-385 (2010) | doi:10.1038/467383a
Careers are made and broken by grant-funding committees. So how are the key decisions really made?
Kendall Powell
http://www.nature.com/news/2010/100922/full/467383a.html
How to get your papers accepted
Muito bom, leitura essencial para alunos de doutoramento:
How to get your papers accepted
só os tópicos:
1. Spellchcek.
2. Get the English right.
3. Make the figures readable!
4. "Related work" is not just a list of citations.
5. Make sure the intro kicks ass.
6. Get to the point.
7. State your contributions!
8. Don't bullshit.
How to get your papers accepted
só os tópicos:
1. Spellchcek.
2. Get the English right.
3. Make the figures readable!
4. "Related work" is not just a list of citations.
5. Make sure the intro kicks ass.
6. Get to the point.
7. State your contributions!
8. Don't bullshit.
Portuguese Research-Universities: Why Not The Best?
Apresentação:
http://www.math.ist.utl.pt/~rfern/athans/
Artigo:
ATHANS, Michael (2002), "Universidades portuguesas: por que não as melhores?”, Gazeta de Física, vol.25, fascículo 1, Abril. Disponível aqui (PDF)
http://www.math.ist.utl.pt/~rfern/athans/
Artigo:
ATHANS, Michael (2002), "Universidades portuguesas: por que não as melhores?”, Gazeta de Física, vol.25, fascículo 1, Abril. Disponível aqui (PDF)
sobre o processo de peer review
Conference reviewing considered harmful
ACM SIGOPS Operating Systems Review
Volume 43 , Issue 2 (April 2009)
This paper develops a model of computer systems research to help prospective authors understand the often obscure workings of conference program committees. We present data to show that the variability between reviewers is often the dominant factor as to whether a paper is accepted. We argue that paper merit is likely to be zipf distributed, making it inherently difficult for program committees to distinguish between most papers. We use game theory to show that with noisy reviews and zipf merit, authors have an incentive to submit papers too early and too often. These factors make conference reviewing, and systems research as a whole, less efficient and less effective. We describe some recent changes in conference design to address these issues, and we suggest some further potential improvements.
ACM SIGOPS Operating Systems Review
Volume 43 , Issue 2 (April 2009)
This paper develops a model of computer systems research to help prospective authors understand the often obscure workings of conference program committees. We present data to show that the variability between reviewers is often the dominant factor as to whether a paper is accepted. We argue that paper merit is likely to be zipf distributed, making it inherently difficult for program committees to distinguish between most papers. We use game theory to show that with noisy reviews and zipf merit, authors have an incentive to submit papers too early and too often. These factors make conference reviewing, and systems research as a whole, less efficient and less effective. We describe some recent changes in conference design to address these issues, and we suggest some further potential improvements.
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