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The professionals were evaluated according three criteria: correct use of PPE; proper fit of PPE in the face ("Seal check"); EPI and conditioning.
For example, several clinicians reported that the clinician education session and the print and EMR versions of the decision tool served as useful prompts or reminders about appropriate prescribing criteria, correct diagnostic codes for bronchitis, and the "true symptoms" of viral and bacterial infections.
All these algorithms suggest that many features of models already in the PDB are likely wrong, but no automated mechanism currently exists to decide if a better modeling of specific areas would be better consistent with the validation criteria, correct these errors where applicable and make the new, corrected models available to the user community.
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Akaike's Information Criteria corrected for a small sample size (AICc) [12], [13] was used to determine which of the two ANCOVA models (A or B) best described the relationship between E (Emet and Emech, CM) and Mb.
In order to ensure that glomeruli were accurately identified, we used the occurrence of double labeling with NCAM and VGlut2 in serial sections through the human OBs as a rigorous and unbiased criteria, corrected with Abercrombie's to further ensure that glomeruli were counted only once.
Significance criteria (corrected t values tcorr) were determined on the basis of permutation tests (Blair and Karniski 1993).
We used jModeltest [ 95] using the Akaike information criteria corrected for small sample sizes (AICc, [ 96]) to determine the best fitting substitution models (GTR + G).
With the same covariates (age, sex, years of education, mcBBR, and rmsFD) and the same statistical criteria (corrected, Z = 2.3, P < 0.05), we found no significant clusters between MDD and healthy controls with volume-based ReHo approach.
We varied the generation at which the breakpoint occurs between G2 and G7 and used the AICc (Akaike's Information Criteria corrected for small sample sizes [ 46]) to compare the models.
In our interpretations, we gave more weight to the Akaike information criteria corrected for sample size because in simulations, it performs better than the Schwarz information criteria when reality is assumed to be infinitely dimensional and the true model is not in the candidate set [ 59].
Sessions were run until the fish reached our training criterion (correct choice frequency of ≥71% in two consecutive sessions).
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CEO of Professional Science Editing for Scientists @ prosciediting.com