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The model RDM was based on All available features model.
The "All available features" model achieved the highest decoding accuracy out of the six models tested.
The semantic coordinates were built using the All available features model (i.e. All available features in the CSLB norm data25).
We focused on the two models that included other features of the target objects than the ones that were explicitly provided in a specific trial (Fig. 2; i.e., Mixed clues (model 5) and "All nonclue features" (model 6)).
Interestingly, the decoding accuracy was higher for the All available features model, combining word2vec vectors over a rich set of features, than the model using the word2vec vector for the target word only.
The best performing model was the "All available features" model, i.e. the one where the resulting semantic coordinates incorporated the combination of all CSLB features of a target object (see also Supplementary Figure 3 for a confusion matrix).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com