Many of these attributes (e.g. Algorithm Type) are not naturally Quantities
Descriptor or Quantifier would be better classifiers for the type

Change Type of Attributes Wrongly Modelled as Quantities

The following attributes need to change their type from QuantityDescriptor to Descriptor:
endorsingOperator
endorsementKind
algorithmType
algorithmValidation
priority

When making a recommendation a level of confidence is give to the accuracy of that recommendation.

When recommendations are deferred to the user and the level of confidence changes through time then a decision aid may wish to send a new/updated recommendation with a higher (or lower) confidence.

This (or another) section could do with some narrative as to the expected model for achieving this: i.e. does the decision aid send a new recommendation and expect the application to detect that a previous recommendation has now been superseded.

Allow update of deferred recommendations

Add Guidance to Response Interface, to state that whilst in the deferred state a recommendation may be update by repeating the recommendation method with the same recommendation id.

The Percentage type does not express how it is to be represented when mapped into a PSM. For example it is represented by a double in DDS. The specification should give advice on whether a percentage is expected to be mapped from 0-100 rather than 0-1 particularly as the type is often used to represent attributes which are named probability.

Clearly state the interpretation of percentage in DDS PSM

Add to description of real-valued quantities in the DDS PSM

It would be useful for a decision aid to be able to supply a rational when making a recommendation as part of the metadata. This would be particularly useful in the marginal cases where a recommendation is deferred to the user to accept so that they can be presented with some information on why the recommendation has been made

This is a duplicate

Issue raised again in error.

Recommendations should enable the supply of a rationale or rule as a descriptor to aid an operator in particular.

Add Rationale to the MetaData for a Recommendation

Add Rationale to the MetaData for a Recommendation (in the properties class)
Model rationale in the style of ALMAS dynamic data:

• have a reference to resource string(s) (that could provide multi-language support)
• have a list of dynamic data with:
  • replacement Tag
  • data type
  • value

The description of the modelProbability attribute in the Confidence class states that this relates to probability given model inputs. There are circumstances where this it would be appropriate for this to be conditional on the broader context as well (i.e. not just on those parameters that are model inputs).
This is about whether the case in point is representative of the training (or design space). Whilst an estimation could be made on how well represented the inputs were in the training set (e.g. are they near a corner case of which there are few prior examples), or it could be known that the current example is from a very different context (e.g. geographical location) from the training set. This would lead to model probability being set low on a somewhat different basis.

Update the notes for model probability to be broader

Clarify that this attribute is representing the degree (likelihood) that the usage of the model in making this making the recommendation is within the design limits of the model. For instance, if it is a trained model, is the usage consistent with the training dataset.