We lifted 2 functions out of this paper's own repositories and ran 1 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| GoogleCloudPlatform/covid-19-open-data | canonical | 1 of 2 |
| Function | Status | Where it lives |
|---|---|---|
| merge_index_dfs | Ran | GoogleCloudPlatform/covid-19-open-data/src/england_data/dataset_merge_util.py code served (permissive licence) · get_code("0de3eb6962c31aae") |
| get_paths_for_given_date | Not yet run | GoogleCloudPlatform/covid-19-open-data/src/england_data/standardize_data.py code served (permissive licence) · get_code("af795f975c723ee3") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
This report describes the aggregation and anonymization process applied to the initial version of COVID-19 Search Trends symptoms dataset (published at https://goo.gle/covid19symptomdataset on September 2, 2020), a publicly available dataset that shows aggregated, anonymized trends in Google searches for symptoms (and some related topics). The anonymization process is designed to protect the daily symptom search activity of every user with $\varepsilon$-differential privacy for $\varepsilon$ = 1.68.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2009.01265")
get_code_for_paper("2009.01265")
have("2009.01265")
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