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

Hello @datacommons-robot-author, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request serves to synchronize the integration test golden files with the current system output. It ensures that the tests remain accurate and up-to-date by incorporating minor, expected numerical variations in the debug_info.json files, which are crucial for validating the detection API's behavior.

Highlights

• Automated Golden File Update: This pull request automatically updates integration test golden files, specifically debug_info.json files, via a Cloud Build process. The changes reflect minor adjustments in expected output values.
• Minor Numerical Adjustments: The updates involve very small, single-digit changes to floating-point numbers within the 'scores' arrays of the affected JSON files, indicating a slight shift in the calculated values.

Changelog

• server/integration_tests/test_data/detection_api_bio/whattypesofgenesarefgfr1,apoe,andache/debug_info.json
  • Updated a floating-point value in the 'scores' array from 0.3797 to 0.37971.
• server/integration_tests/test_data/detection_api_multivar/howarefactorslikeobesity,bloodpressureandasthmaimpactedbyclimatechange/debug_info.json
  • Updated a floating-point value in the 'scores' array from 0.6305 to 0.63049.

Activity

• This pull request was automatically created by the datacommons-robot-author.
• The changes were generated by a Cloud Build process, as indicated by the provided log link.
• The primary activity is the automated update of golden files for integration tests.

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[gemini-code-assist]

Code Review

This pull request updates golden test files with minor changes to floating-point scores. While this is an automated update, increasing the precision of these scores can make tests more brittle and sensitive to insignificant model variations. There is a repository guideline to round floating-point scores to a consistent, lower precision to improve test robustness. I've left specific comments suggesting rounding the updated values. It would be beneficial to update the automation script to handle this rounding automatically in the future.

[gemini-code-assist]

To improve test stability and reduce noise from minor model output variations, it's recommended to round floating-point scores to a consistent, lower precision. Rounding this value to 4 decimal places would align with the previous value and make the test less brittle.

Suggested change

	0.37971
	0.3797

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.

[gemini-code-assist]

To improve test stability and reduce noise from minor model output variations, it's recommended to round floating-point scores to a consistent, lower precision. Rounding this value to 4 decimal places would align with the previous value and make the test less brittle.

Suggested change

	0.63049,
	0.6305,

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.