To analyze the relationship between the feature "ritm_ecg_p_02" and the task of detecting chronic heart failure, we need to examine how the presence or absence of atrial fibrillation (AF) in the patient's ECG rhythm at the time of admission relates to the likelihood of chronic heart failure.

Rhythm disturbances like atrial fibrillation can potentially contribute to the development or exacerbation of chronic heart failure. Therefore, it is reasonable to assume that patients with atrial fibrillation (AF = "yes") have a higher probability of showing chronic heart failure compared to patients without atrial fibrillation (AF = "no").

Based on this analysis, the dictionary representation would be:

```json
{
	"no": ["no"],
	"yes": ["yes"]
}
```

This indicates that for patients who do not have atrial fibrillation (AF = "no"), the possible values for the feature "ritm_ecg_p_02" are solely "no". Similarly, for patients with atrial fibrillation (AF = "yes"), the only possible value for the feature is "yes".

Note: Since the feature "ritm_ecg_p_02" is binary (either "yes" or "no"), there is no ambiguity in the mapping between its values and the target class of chronic heart failure.