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Software for reproducible science: let’s not have a misunderstanding

Gaël Varoquaux · published 17 May 2015

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1blogs citing
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14 May 2018
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14 May 2018
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shape-of-code.com
Replicating results using research software Read at the source ↗
14 May 2018

Links from this post

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https://twitter.com/ctitusbrown/status/589171853031186434
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http://en.wikipedia.org/wiki/Growth_in_a_Time_of_Debt
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http://www.bbc.com/news/magazine-22223190
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http://www.cell.com/neuron/abstract/S0896-6273%2808%2900958-6
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http://nilearn.github.io/auto_examples/decoding/plot_miyawaki_reconstruction.html
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http://nilearn.github.io
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http://scikit-learn.org/stable/
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https://github.com/nilearn/nilearn/issues?q=is%3Aissue+is%3Aclosed
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http://blog.codinghorror.com/the-prototype-pitfall/
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http://jmlr.org/papers/volume15/delgado14a/delgado14a.pdf
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http://ieeexplore.ieee.org/Xplore/login.jsp?url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F32%2F35909%2F01702600.pdf%3Farnumber%3D1702600&authDecision=-203
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