Add min/max value constraints to score and confidence slots. (#373)

Resolves #372

- [ ] `docs/` have been added/updated if necessary (not applicable; the
doc was already ahead of the model, this PR is about updating the model
to align it with the doc)
- [x] `make test` has been run locally
- [ ] tests have been added/updated (not applicable)
- [x]
[CHANGELOG.md](https://github.com/mapping-commons/sssom/blob/master/CHANGELOG.md)
has been updated.

The description of the `confidence`, `semantic_similarity_score`, and
`similarity_score` slots says that those slots expect a value between 0
and 1, but the model does not enforce that. LinkML provides a way to
formalise this kind of value constraints (which could then be
automatically enforced by a runtime that is aware of those constraints),
so we do exactly that here: we add `minimum_value` and `maximum_value`
constraints to the aforementioned slots.

CHANGELOG.md

@@ -7,6 +7,7 @@
 ## SSSOM version 0.15.1
 
 - Add recommendation to sort the keys in the YAML metadata block.
+- Double-typed slots explicitly constrained to the [0.0,1.0] range, as per their description.
 
 ## SSSOM version 0.15.0
 

src/sssom_schema/schema/sssom_schema.yaml

@@ -479,6 +479,8 @@ slots:
     description: A score between 0 and 1 to denote the confidence or probability that
       the match is correct, where 1 denotes total confidence.
     range: double
+    minimum_value: 0.0
+    maximum_value: 1.0
   subject_match_field:
     description: A list of properties (term annotations on the subject) that was used
       for the match.
@@ -558,6 +560,8 @@ slots:
     description: A score between 0 and 1 to denote the semantic similarity, where
       1 denotes equivalence.
     range: double
+    minimum_value: 0.0
+    maximum_value: 1.0
   semantic_similarity_measure:
     description: The measure used for computing the the semantic similarity score.
       To make processing this field as unambiguous as possible, we recommend using 
@@ -570,6 +574,8 @@ slots:
     description: A score between 0 and 1 to denote the similarity, where
       1 denotes equivalence.
     range: double
+    minimum_value: 0.0
+    maximum_value: 1.0
   similarity_measure:
     description: The measure used for computing the the similarity score.
       To make processing this field as unambiguous as possible, we recommend using