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Seafloor Density Measurements, Prediction, and Associated Uncertainty for "Predicting global marine sediment density using the random forest regressor machine learning algorithm"

<p>Global seafloor density prediction results using the random forest regressor machine learning algorithm.&nbsp;</p> <p>Dataset S1.&nbsp;Seafloor density measurements.&nbsp; Columns are labeled with a header and include associated drilling project and measurement type for each sample.&nbsp;&nbsp;File format: CSV text file</p> <p>Dataset S2. Seafloor density prediction results from the random forest regressor machine learning algorithm at 5&times;5-arc minute resolution.&nbsp; Units are g/cm^3.&nbsp; File format: netCDF (.nc)</p> <p>Dataset S3. Seafloor density prediction standard deviation from the random forest regressor machine learning algorithm at 5&times;5-arc minute resolution.&nbsp; Units are g/cm^3.&nbsp; File format: netCDF (.nc)</p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
20
Reuse readiness
8
Engagement
0