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The design procedure follows a methodology called design space approach.
The identification procedure follows a specially designed Least Squares (LS) technique.
The proposed procedure follows a pattern of eliciting, challenging, and self-reviewing stakeholder perspectives that aims to facilitate learning.
The spatial warping procedure follows a methodology based on least-squares estimation to correct the non-linear distortion in the endoscopic images.
To identify experts for ECs, the procedure follows a product data analytics (PDA) approach that uses PDM databases as its operational data source to analyze different aspects of product development processes managed by PDM systems.
Our procedure follows a 10-fold cross-validation scheme [43]: the real dataset is divided into 10 parts or folds, and for each fold we use the 10% of the target values as test set, and the remaining 90% as training set.
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This procedure follows an established protocol as used e.g. in [ 32– 34], and the resulting tumor phenotype has been extensively studied [ 33, 34].
The estimation procedure followed a two-phase sampling design grounded within a hybrid inferential framework, which combines design-based estimation for the first phase and model-based inference in the second phase.
The staining procedure followed a standard protocol.
The prediction procedure followed a sequence of three steps.
The ISH procedure followed a previously published protocol [ 13].
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