Sentence examples for incorrectly categorized from inspiring English sources

Exact(26)

Incorrectly categorized or unrecognized calls are screened before ringing through to the user.

In a statement, Bard said that it had not submitted those reports to mislead the agency but said that the company had incorrectly categorized the complaints based on the information it had at the time.

Rumer Godden, who is incorrectly categorized as a children's writer, and who writes with so much understatement that readers can miss the depth of her insight and her vivid grace.

Users can also quickly manually tag data that's incorrectly categorized.

Twenty-five percent of all non-responders were incorrectly identified, while only 7% of all improvers were incorrectly categorized as non-responders using this cutoff.

As Kemp's book explains, for decades after their collection, specimens housed in museum archives can remain incorrectly categorized, or not categorized at all not only due to the sheer size of some of these collections, but also the complex detective work that must go into proper taxonomic classification.

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Similar(34)

Lower gaydar accuracy for men's faces was explained by a difference in "false alarms": participants were more likely to incorrectly categorize a straight man as gay than to incorrectly categorize a straight woman as gay.

However, these approaches (i) can incorrectly categorize a fishery as over-exploited or collapsed due to single or multiple years of anomalous high catch and (ii) require all non-declining fisheries to be categorized as fully-exploited by the end of the time series.

The more STIs tested, the smaller the risk of incorrectly categorizing individuals as mono-infected.

Thus, using the MPI interception database in conjunction with the mtDNA data decreases the potential for incorrectly categorizing the type of detection that each intercepted L. delicata represents.

In fact, the algorithm was more likely to wrongly categorize white defendants as low-risk while black defendants were often incorrectly labeled as high-risk.

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