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The systematic terms are dominating in the retrieval error budget.
PubMed abstracts frequently contain novel trivial and semi systematic terms.
Therefore grammar-based approaches can extract systematic terms that are missing from the dictionaries.
Grammar-based approaches expand their extractions through the capture of systematic terms by utilizing these sets of rules, for example by means of finite state machines [7].
In a later study Lowe et al. [16] further improved dictionary-based approaches by introducing 485 grammar-based rules to identify systematic terms.
From a total of 37469 TPs captured by the ensemble system, 4139 cases were unique to ChEBI (mostly formula and abbreviation), 1878 were unique to HMDB (mostly trivial and abbreviation), 9480 cases were unique to LeadMine (mostly systematic terms) and 280 cases were unique to Regular expressions.
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These predefined grammars are sets of rules or guidelines developed to refer to a compound with a unique textual representation (systematic term or identifier).
Following common practice [2], we assume that the observable utility U ij (say) consists of the systematic term V ij and some random disturbance term e ij, i. e. {U}_{ij}={V}_{ij}+{e}_{ij}, (5 where the e ij are independent and identically Gumbel distributed random variables with scale parameters μ j.
We estimated the following model for the latent utility U for a CRC screening alternative: U = V + ϵ = β 0 + ∑ i = 1 24 β i x i + ϵ V is an explainable, systematic term specified as a linear function of the CRC screening alternatives.
Residuals then form the measurement of efficiency and the error term is divided into a stochastic error term and a systematic inefficiency term.
While such developments have been investigated in short-term trials, no systematic long-term investigations of the microhardness variation as a function of microstructural development have been presented.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com