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The phrase "a positive token" is correct and usable in written English.
It can be used in contexts where you are referring to a symbol or representation of something positive, such as in discussions about psychology, rewards, or digital currencies.
Example: "In our team meetings, we often give a positive token to members who have gone above and beyond in their work."
Alternatives: "a positive symbol" or "a favorable token".
Exact(2)
Gann et al. [28] selected 6,799 tokens based on Twitter data, where each token is assigned a sentiment score, namely TSI(Total Sentiment Index), featuring itself as a positive token or a negative token.
All in all, these studies agreed with the idea that OA would act as a positive token, signalling a positive reward in an appetitive conditioning.
Similar(58)
Figure 4 Sentiment score information for word tokens (a) Positive word tokens (b) Negative word tokens.
If there are more positive tokens than negative ones, the sentence will be tagged as positive, and vice versa.
The dynamic evolution of the system is described by tokens: at any time, each place holds zero or a positive number of tokens.
All it took to make a positive impression were my token gestures of smiling, saying hello and small talk -- and doing so in equal measure with every student in the room.
Given those sentiment words proposed in [27], a word token consists of a positive (negative) word and its part-of-speech tag.
By the same token, it penalizes inappropriate decisions to reduce the probability of assigning an inappropriate label by imposing a positive cost U.
By the same token, those who were once on the receiving end of British imperial invasions are less likely than us to view them in a positive light.
This model is based on a neural network that assigns scores to windows of 11 tokens and learns to output values for positive examples (token windows extracted from a corpus) higher than for negatives ones (random perturbations of positive examples).
This process resulted in 65 tokens of Evoked laughter (Speaker A: 14 tokens, Speaker B: 32, Speaker C: 19 tokens; mean duration: 4.14 s), 60 tokens of Emitted laughter (Speaker A: 17 tokens, Speaker B: 17 tokens, Speaker C: 26 tokens; mean duration 2.98 s), and 52 tokens of Disgust (Speaker A: 16 tokens, Speaker B: 16 tokens, Speaker C: 19 tokens; mean duration 1.70 s).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com