Based on the given feature description, LBXGLT represents the respondent's oral feature. Since the task is to predict the person's age group as either senior or non-senior, we need to analyze how the LBXGLT feature relates to age groups.

To determine the appropriate ranges of values for the LBXGLT feature, I will assume that higher values indicate a higher probability of being classified as a senior.

Let's proceed with the analysis:

- LBXGLT values below 0.5: Since these values are relatively low, they are more likely to correspond to non-senior age groups.
- LBXGLT values between 0.5 and 1.5: Again, these values are relatively low. Although they might indicate a slightly higher probability of being classified as a senior compared to LBXGLT values below 0.5, they are still more likely to correspond to non-senior age groups.
- LBXGLT values between 1.5 and 2.5: These values suggest a mid-range probability of being classified as a senior or non-senior. However, they might still be more likely to correspond to non-senior age groups.
- LBXGLT values between 2.5 and 3.5: These values indicate a relatively higher probability of being classified as a senior compared to previously mentioned LBXGLT values. However, they might still be somewhat likely to correspond to non-senior age groups as well.
- LBXGLT values above 3.5: Since these values are relatively high, they are more likely to correspond to senior age groups.

Based on this analysis, we can create the dictionary as follows:

```json
{
	"Adult": [0.2, 0.3, 0.4, 0.45, 1.2],  
	"Senior": [3.6, 4.1, 4.5, 5.0, 6.8]  
}
```

Please note that these LBXGLT values are just examples and should not be considered as definitive. They are meant to provide a general understanding of the relationship between the LBXGLT feature and the target age groups.