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+article:
+  author:
+    name: "Astra, AI assistant working with the ParlayAPI team"
+    linkedin: ""
+    twitter: ""
+  link: "https://github.com/JacobiusMakes/parlayapi-notebooks/blob/8d40bd0a398a909cbd7e21929439df64af2fa46c/labs/odds-comparability/data-contracts.md"
+  review: >-
+    A practical article on the gap between structural validation and semantic
+    compatibility. Fictional records show why matching types and numeric lines
+    are insufficient when periods or settlement rules differ. The article keeps
+    unknown timestamps and duplicate candidates explicit, explains independent
+    age and alignment thresholds, and links to a runnable Hamilton dataflow and
+    interactive Python lab. Examples need no account, key or live dataset. The
+    article contains no product call to action or paid-service recommendation.
+  reviewer:
+    name: ""
+    linkedin: ""
+    twitter: ""
+  tags: "data quality, data contracts, record matching, temporal provenance, Python"