[ML] Discrepancy between the typical values in the record and anomaly_score_explanation

[valeriy42]

There is a discrepancy between the typical values in the records and in the anomaly_score_explanation. This may be ligitamite, but then it's confusing since both fields have similar names. We need to investigate where the discrepancy comes from.

Example:

{
      "job_id": "logs-2",
      "result_type": "record",
      "probability": 1.3270118176914605e-10,
      "multi_bucket_impact": -5,
      "record_score": 98.23845097090914,
      "initial_record_score": 98.23845097090914,
      "bucket_span": 900,
      "detector_index": 0,
      "is_interim": false,
      "timestamp": 1744461000000,
      "function": "count",
      "function_description": "count",
      "typical": [
        6.350539918419784
      ],
      "actual": [
        63
      ],
      "anomaly_score_explanation": {
        "anomaly_type": "spike",
        "anomaly_length": 1,
        "single_bucket_impact": 13,
        "anomaly_characteristics_impact": 7,
        "lower_confidence_bound": 1.950348036227763,
        "typical_value": 6.273279374077203,
        "upper_confidence_bound": 13.662117549841197,
        "high_variance_penalty": true,
        "multimodal_distribution": true,
        "by_field_relative_rarity": 1
      },
      "ip": [
        "30.156.16.163"
      ],
      "clientip": [
        "30.156.16.164"
      ]
    }