Automated Integration Test Goldens Update from CI

[datacommons-robot-author]

This pull request updates the golden files automatically via Cloud Build. Please review the changes carefully. Cloud Build Log

[gemini-code-assist]

Summary of Changes

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This pull request contains an automated update to the integration test golden files, ensuring that the test data remains synchronized with the latest changes in the application's output.

Highlights

• Golden File Update: Updated the chart configuration for the 'stateswithhighestphds' integration test to include a new classification entry.

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[gemini-code-assist]

Code Review

This pull request updates the test data configuration in chart_config.json by adding a new classification entry that includes a quantity filter. A review comment points out that the floating-point value used (2.2250738585072014e-308) is likely an uninitialized minimum value and suggests replacing it with 0.0 to ensure test robustness and follow precision guidelines.

[gemini-code-assist]

The value 2.2250738585072014e-308 is suspicious. This value is equivalent to sys.float_info.min, the smallest positive normalized double-precision number. Its presence here strongly suggests a potential bug in the quantity detection logic, where an uninitialized or default value might be leaking into the results.

According to our guidelines, floating-point values in test data should be rounded to a lower precision to make tests more robust. This extremely precise and small number is likely unintended.

If the goal is to filter for values greater than or equal to zero, 0.0 would be a much clearer and more stable choice.

Suggested change

	"val": 2.2250738585072014e-308
	"val": 0.0

References

1. Round floating-point scores in test data to a consistent, lower precision. This makes tests more robust against insignificant model output variations and reduces review noise.

[shixiao-coder]

LGTM