Примери за използване на Galaxy zoo на Английски и техните преводи на Български
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Galaxy Zoo Prior.
Fletcher( 2015) Building on Galaxy Zoo.
Galaxy Zoo Helping science, fun, community.
A few months later, Galaxy Zoo was born.
For the Galaxy Zoo team, this first project was just the beginning.
Almost 2 years ago, Galaxy Zoo was born.
In Galaxy Zoo, there were about 40 classifications per galaxy; .
To make this a bit more concrete,let's return to Galaxy Zoo.
Galaxy Zoo is a good illustration of how many human computation projects evolve.
The prototypical example of a human computation project is Galaxy Zoo.
At the Galaxy Zoo website, volunteers would undergo a few minutes of training;
Recall, that Schawinski andLintott were graduate students when they started Galaxy Zoo.
Not only is the microtask in Galaxy Zoo quite general, but the structure of the project is general as well.
Imagine Kevin Schawinski and Chris Linton,two astronomers sitting in a pub in Oxford thinking about Galaxy Zoo.
Galaxy Zoo combined the efforts of many non-expert volunteers to classify a million galaxies. .
The prototypical example of a human computation project is Galaxy Zoo, which I will describe in detail below.
Galaxy Zoo launched in 2007, with an initial one million images for people to classify.
It is pretty cool that citizen scientists have labeled galaxies at Galaxy Zoo and folded proteins at Foldit.
For example, the Galaxy Zoo community has discovered a new class of astronomical object that they called“Green Peas.”.
None of this was ever imagined when Kevin Schawinski andChris Lintott first discussed Galaxy Zoo in a pub in Oxford.
This comparison shows that, as with Galaxy Zoo, human computation projects can produce high-quality results.
Because very similar challenges arise in most human computation projects,it is helpful to briefly review the three steps that the Galaxy Zoo researchers used to produce their consensus classifications.
Fortunately, Galaxy Zoo enabled these kinds of unexpected surprises by allowing participants to communicate with each other.
If this model could reproduce the human classifications with high accuracy,then it could be used by Galaxy Zoo researchers to classify an essentially infinite number of galaxies. .
For example, in Galaxy Zoo the researchers could have shown each galaxy until there was agreement about its shape.
Finally, on July 8, 2008- almost a fullyear later- Carolin Cardamone, an astronomy graduate student at Yale and member of the Galaxy Zoo team, joined the thread to help organize the“Pea Hunt.”.
For example, in Galaxy Zoo the researchers could have shown each galaxy until there was agreement about its shape.
The work of Banerji andcolleagues turned Galaxy Zoo into what I would call a computer-assisted human computation system.
When these Galaxy Zoo classifications were compared with three previous smaller-scale attempts by professional astronomers, including the classification by Schawinski that helped to inspire Galaxy Zoo, there was strong agreement.
Thus, after a three-step process- cleaning, debiasing,and weighting- the Galaxy Zoo research team had converted 40 million volunteer classifications into a set of consensus morphological classifications.