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After 50 singers were selected, the decision to do "The Mysteries" (or "Yiimimangaliso," in Zulu) was easier: since most South Africans are Christians, they already knew the stories of the Bible.
To remove individual biases in confidence, their confidence estimates were normalised, so that they shared the same mean and standard deviation, before being submitted to the Maximum Confidence Slating (MCS) algorithm, which selected the decision of the more confident member of the virtual dyad on every trial.
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In selecting the decision variables, the category of inputs and outputs considered is in accordance with the views of the university's stakeholders in relation to its contribution to the overall efficiency of a department.
For example, for 2-bit/cell flash memories, the errors of page 1 will be symmetric if we select the decision level D ̂ 1, 2 between S1 and S2 which makes Q Δ 1, 1 σ 1, 1 = Q Δ 2, 0 σ 2, 0 in (6).
Third, what is the effect of normalising confidence estimates before selecting the decision made with higher confidence?
The MCS algorithm effectively implements the WCS model by selecting the decision made with higher confidence (cf. the Δ c ∼ / σ ratio of higher magnitude) on each trial.
To test the effect of normalising confidence estimates before selecting the decision made with higher confidence, we also submitted raw confidence estimates to the MCS algorithm.
The trials in which dyad members reported the same level of confidence but selected different intervals were resolved by randomly selecting the decision of one of the two dyad members; we note that there were no such confidence ties when submitting normalised confidence estimates to the MCS algorithm.
Firstly, we selected the best decision tree structure for each emotion model as shown in Table 4.
Five physicians staffing our Centre, including two authors of the report (PVR and SC) selected the issues in the decision to prescribe in consensus and rephrased them into questionnaire items faithful to the original formulation.
If a wrong node is selected at an early iteration because it gives the best quality of fit for the selected node, the decision cannot be reconsidered at later iterations taking into account additional links created after that wrong decision.
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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