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Normalize mixed thumbs-and-stars feedback into a single actionable metric for model evaluation and monitoring. Follow a compact Python pipeline to convert signals, aggregate by run, surface worst examples, compute weighted averages, and gate releases with a pass rate. Practical outcome: faster issue discovery, clearer triage lists, and dashboard-ready metrics for CI and production monitoring. #Python #AIEngineering #LLM #MLOps #ModelEvaluation #Tutorials — Subscribe for concise AI engineering and LLM system tutorials.