Worth noting that the original paper mentions several potential reasons to prefer the status quo, which can in fact be valid arguments rather than bias. Your body temperature example is an instance of the first one, the argument from evolutionary adaptation:
Obviously, the Reversal Test does not show that preferring the status quo is always unjustified. In many cases, it is possible to meet the challenge posed by the Reversal Test and thus to defeat the suspicion of status quo bias. Let us examine some of the possible ways in which one could try to do this [...]
The Argument from Evolutionary Adaptation
For some biological parameters, one may argue on evolutionary grounds that it is likely that the current value is a local optimum. The idea is that we have adapted to live in a certain kind of environment, and that if a larger or a smaller value of the parameter had been a better adaptation, then evolution would have ensured that the parameter would have had this optimal value. For example, one could argue that the average ratio between heart size and body size is at a local optimum, because a suboptimal ratio would have been selected against. This argument would shift the burden of proof back on somebody who maintains that a particular person’s heart—or the average human heart-tobody-size ratio—is too large or too small. [...]
The Argument from Transition Costs
Consider the reluctance of the United States to move to the metric system of measurement units. While few would doubt the superiority of the metric system, it is nevertheless unclear whether the United States should adopt it. In cases like this, the transition costs are potentially so high as to overwhelm the benefits to be gained from the new situation. Those who oppose both increasing and decreasing some parameter can potentially appeal to such a rationale to explain why we should retain the status quo without having to insist that the status quo is (locally) optimal. [...]
The Argument from Risk
Even if it is agreed that we are probably not at a local optimum with respect to some parameter under consideration, one could still mount an argument from the risk against varying the parameter. If it is suspected that the potential gains from varying the parameter are quite low and the potential losses very high, it may be prudent to leave things as they are (fig. 2).
Worth noting that the original paper mentions several potential reasons to prefer the status quo, which can in fact be valid arguments rather than bias. Your body temperature example is an instance of the first one, the argument from evolutionary adaptation: