Unboxing the SHAP

One of the reasons behind the magic of XAI (Explainable AI) tools like SHAP, is the ability to display not only the overall importance of predictor features behind a model, but also the specific importance and relationship between input features and one specific model's output or prediction.

The following plot depicts the importance played by red wine chemical properties (predictor features) in estimating its quality (output), for a given wine observation (data instance). The resulting model prediction is a quality level of 0.16 for this wine.

Below are four statements related to feature importance and model behavior in this individual prediction.

One of these statements is False. Can you find it?