A machine-learning model can predict molecular assembly scores from single-stage mass spectra with roughly three times lower error than baseline models, supporting the use of mass spectrometry as an agnostic biosignature measurement.
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Exploring molecular assembly as a biosignature using mass spectrometry and machine learning
A machine-learning model can predict molecular assembly scores from single-stage mass spectra with roughly three times lower error than baseline models, supporting the use of mass spectrometry as an agnostic biosignature measurement.