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CS has similar problem, specially in AI fields. Researches often claim the accuracy rate more than 95%, but in reality that is much lesser (in fact less than 10% in most of the claims).



Yes, that's why I no longer consider pursuing PhD in CS. It's a waste of life to reproduce non-reproducible papers that is full of buzzword.

Hopefully, more journals and confs will follow the Open Access and Reproducible Research model like IPOL[1].

> Each article contains a text describing an algorithm andsource code, with an online demonstration facility and an archive of online experiments. The text and source code are peer-reviewed and the demonstration is controlled.

[1]http://www.ipol.im/


Having worked in computer vision and robotics, I can attest to this.


Yes. Of the fields I've implemented algorithms from papers in, computer vision seems to be particularly adverse to discussing the (often critical) downsides of their algorithms. Often its something like "Camera calibration isn't exactly perfect? Well this scene reconstruction technique simply wont work."




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