Color space, put simply, is a mathematical description of color. It is used to represent color in ways that are appropriate to the display
device being used, and to account for the range of colors that the particular device is capable of achieving (the “color gamut”). When
working with Red images, Red has predefined a few color spaces for use when converting RAW images to RGB images. These color space
models are basically intended to provide color values in the converted image that are appropriate for various display methods, based on the general characteristics of those displays (in particular their white point), and their specific color gamut. Essentially, the values that are the result of the debayering process are further altered by each of the color space settings (in both value and saturation) to achieve more
accuracy to the “real world” colors that were present when the images were captured by the sensor, based on the characteristics of the
intended display system. At this point, the color space choices (they are actually color matrixes, and can be described by either term), and their effects on the image, that are currently offered by Red are:

Camera RGB: This matrix passes the RGB values as described above and does not modify them based on any particular display technology.

Rec709: This matrix alters the resulting RGB values to, in theory, properly display an accurate representation on an HD video display. It also seems to add quite a bit of saturation, and because of that, is rarely used.

Redspace: This matrix appears to be similar to Camera RGB, but with a mild saturation boost

At this point, the best choices for most projects seem to be Camera RGB and Redspace, with Red Space  / Camera RGB will be the preferred color space for many people including major VFX post house

Gamma:

Like most electronic sensors, the Mysterium sensor represents the world in what we would call Linear Light. In a linear light representation, absolute values are obtained based on the brightness of the elements of the image.

Each chip is twice as bright as the previous one. However, human eyes do not perceive this accurately. For instance, in theory, the brightest grey chip is actually 64 times as bright as the darkest chip – yet it doesn’t  “look” that way. Additionally, if a linear light image is observed directly on an electronic display, it will look much too dark, because electronic displays are not designed to display linear light. Displays have a gamma characteristic – in other words, they are nonlinear, particularly in the darkest areas. There are a number of technical reasons for this, but suffice it to say that in order for an image to display properly, it must have the same gamma characteristic as the display being used. In order to make the image more “perceptually linear” on  a specific type of display (one might call this “linear luminance” rather than “linear light”), the values are altered by a luminance curve that effectively boosts the lower values in a nonlinear way. The value of this curve is the gamma, and in most cases, it is designed to match the gamma characteristic of the display system. Another option is to encode the linear light values to logarithmic values, which has the effect of redistributing the available value levels. providing more available values at the lower and middle end of the scale, and fewer at the high end - much the way human eyes perceive light. By making the lower values more precise, and the higher values less precise, it also allows you to fit more useful information into fewer bits, allowing, for instance, the 12 bit linear light information provided by the sensor to comfortably be represented in a 10 bit file. And finally, it has the advantage of representing the scene in values that are more like negative film, which also has a logarithmic response. It must be noted, however, that a logarithmically coded image will not look correct on most electronic displays without the use of a lookup table (discussed below).