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Perturbation from external systems may produce false or very biased values of the metrics.
However, overcorrection of these potential confounding factors may produce false negative errors (Brachi et al. 2011; Korte & Farlow 2013).
This assumption is invalid because a node can send false location information too and may produce false results [64].
Also asking the experts to assign scores ranging from 1 to 10 for different risks considered may produce false and unrealistic impression (Kumru and Kumru 2013).
However, current automated testing techniques may produce false positives (or false negatives) even in a perfectly working system because the outcome of a test case depends on the state of the database which changes over time as data is inserted and deleted.
Furthermore, both methods may produce false predictions due to experimental deficiencies: for IHC-based classification, false negatives may arise from experimental or subjective errors detailed above.
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On the other hand, low-grade malignant tumours, such as carcinoid [11] or low-grade adenocarcinoma [12], may produce false-negative results because of their low glucose metabolism.
As Bloom filters may produce false-positives but never false negatives, when a filter does not match a segment, i.e., m i ∈M indicates a mismatch, the algorithm can safely skip to the next Bloom filter fi−1 (if i≥2) without touching its associated hash table t i.
However, infection with other flaviviruses may produce false-positive serologic results.
It requires a high density of bacteria, and anything that reduces the bacterial load may produce false-negative tests.
Alternatively, sexual maturation or low infection intensity of E. multilocularis may produce false-negative results in PCR assays (8 ).
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