Sentence examples similar to score information such from inspiring English sources

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Other methods of aggregation of z-score information, such as sums of absolute values or PA scores [ 38], performed poorer and were therefore not considered.

Generally speaking, a method that could score contextual information, such as gene order, taxonomy, domain order… would be extremely powerful.

Apart from the EP score, a second score, EPclin, has been developed, which combines the EP score with clinical information, such as nodal status and tumor size.

With the help of this number and publicly available information, Spacek would just need to answer two laughably simple questions at United Airlines to immediately create a new password for the victim's account that's the jackpot, because from there, he could score other relevant information, such as payment information, reservations, and addresses, as well as one or two free flights.

Enter or edit future MCAT tests dates here along with your test scores and any additional test information such as scores from the GRE is applicable.

In order to score the different categories of information such as binary counts and quantitative gene expression values, we summarized the scores of the individual experiments for each category.

Multiple categories of data online payment data, social network data, e-commerce purchase data, and other information such as application scores, response scores, anti-fraud scores are all used to generate a profile for each individual".

The paper assessment quizzes were destroyed after the questions were graded, with only non-identifying information such as scores on the assessments retained for research purposes.

Users will receive a score-keeping application and other information such as statistics, rosters, lineups, pitching match-ups and biographies.

Lenders make use of "hard" information, such as credit score, debt-to-income ratio, and annual income, and "soft" information, such as a borrower's picture or a textual description of the future plan (Iyer et al. 2009), to infer borrowers' creditworthiness.

This is to be expected, as our approach uses a merged set of alignments and leverages more information, such as quality score and linking, to decide the origin labels.

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