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Specifically, self-efficacy was predicted to have a positive effect on persistence given unambiguous feedback, but a weak, negative effect given ambiguous feedback.
Study 1 involved the development and validation of a measure of appearance-based cognitive bias, the Physical Appearance Ambiguous Feedback Scale (PAAFS).
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The effect of the spatial relation between cue and reward (a direct one in solid objects and an ambiguous visuospatial feedback on the touchscreen), promoting repeated responses towards the unrewarded stimulus, is also reflected in the greater number of errors on the touchscreen.
Therefore, given the limitation of familiarity biases and ambiguous digestive feedbacks, copying helps individuals obtain "selected" information from neighbors.
Moreover, in the algorithm, feedbacks from digestion of resource mixtures are averaged over all resources consumed, making feedbacks ambiguous, as appears to be the case in some diet development studies (e.g., Duncan and Young 2002).
At the same time, increased mixing of resources means that feedbacks from digestion are more often ambiguous because the energy feedback is averaged over all resource items (see Eq. 1).
In literature, one can find a variety of expectations about the ambiguous ways in which feedback influences self-regulation.
One possibility is that biased interpretation is installed by anxious parents who, due to their own interpretation bias, frequently provide negative feedback about ambiguous stimuli and situations to their children.
For the purposes of the present study, this paradigm provides a robust measure of judgment bias, determining whether individuals overestimate (i.e. are positively biased), underestimate (i.e. are negatively biased), or are accurate about their performance in an ambiguous context where no feedback is provided.
Based on feedback from the pupils, ambiguous questions were either reframed or removed and difficult words were re-worded.
This is likely due to the fact that the criteria were clarified and made less ambiguous (as a result of reviewer feedback), as well as due to the growing experience (and competence) of the pool of regular CAEP abstract reviewers.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com