Job request: 23921
- Organisation:
- King's College London
- Workspace:
- incidence_longtermconditions
- ID:
- 26jr7deui534k2yx
This page shows the technical details of what happened when the authorised researcher Mark Russell requested one or more actions to be run against real patient data in the project, within a secure environment.
By cross-referencing the list of jobs with the
pipeline section below, you can infer what
security level
various outputs were written to. Researchers can never directly
view outputs marked as
highly_sensitive
;
they can only request that code runs against them. Outputs
marked as
moderately_sensitive
can be viewed by an approved researcher by logging into a highly
secure environment. Only outputs marked as
moderately_sensitive
can be requested for release to the public, via a controlled
output review service.
Jobs
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- Job identifier:
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fxuuze2njtbj662z
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ttcehv4jqm2ogw4x
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nw5zy4bgpytmt5q7
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ctscpludlp3w55ns
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gurjvvxhb7kg6szx
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- Job identifier:
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un5xfkgwkmdehiq5
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hc4xx5t5whef334u
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aihf6patg5ai2cul
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- Job identifier:
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53hn4ppncyvw7bii
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- Job identifier:
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57zu4ay54c4lduge
Pipeline
Show project.yaml
version: '3.0'
expectations:
population_size: 10000
actions:
generate_dataset:
run: ehrql:v1 generate-dataset analysis/dataset_definition.py
--output output/dataset_definition.csv
outputs:
highly_sensitive:
cohort: output/dataset_definition.csv
measures_dataset_2016:
run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
--output output/measures/measures_dataset_2016.csv
--
--start-date "2016-03-01"
--intervals 12
needs: [generate_dataset]
outputs:
highly_sensitive:
measure_csv: output/measures/measures_dataset_2016.csv
measures_dataset_2017:
run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
--output output/measures/measures_dataset_2017.csv
--
--start-date "2017-03-01"
--intervals 12
needs: [generate_dataset]
outputs:
highly_sensitive:
measure_csv: output/measures/measures_dataset_2017.csv
measures_dataset_2018:
run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
--output output/measures/measures_dataset_2018.csv
--
--start-date "2018-03-01"
--intervals 12
needs: [generate_dataset]
outputs:
highly_sensitive:
measure_csv: output/measures/measures_dataset_2018.csv
measures_dataset_2019:
run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
--output output/measures/measures_dataset_2019.csv
--
--start-date "2019-03-01"
--intervals 12
needs: [generate_dataset]
outputs:
highly_sensitive:
measure_csv: output/measures/measures_dataset_2019.csv
measures_dataset_2020:
run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
--output output/measures/measures_dataset_2020.csv
--
--start-date "2020-03-01"
--intervals 12
needs: [generate_dataset]
outputs:
highly_sensitive:
measure_csv: output/measures/measures_dataset_2020.csv
measures_dataset_2021:
run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
--output output/measures/measures_dataset_2021.csv
--
--start-date "2021-03-01"
--intervals 12
needs: [generate_dataset]
outputs:
highly_sensitive:
measure_csv: output/measures/measures_dataset_2021.csv
measures_dataset_2022:
run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
--output output/measures/measures_dataset_2022.csv
--
--start-date "2022-03-01"
--intervals 12
needs: [generate_dataset]
outputs:
highly_sensitive:
measure_csv: output/measures/measures_dataset_2022.csv
measures_dataset_2023:
run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
--output output/measures/measures_dataset_2023.csv
--
--start-date "2023-03-01"
--intervals 12
needs: [generate_dataset]
outputs:
highly_sensitive:
measure_csv: output/measures/measures_dataset_2023.csv
measures_dataset_2024:
run: ehrql:v1 generate-measures analysis/dataset_definition_measures.py
--output output/measures/measures_dataset_2024.csv
--
--start-date "2024-03-01"
--intervals 6
needs: [generate_dataset]
outputs:
highly_sensitive:
measure_csv: output/measures/measures_dataset_2024.csv
run_incidence_graphs:
run: stata-mp:latest analysis/100_incidence_graphs.do
needs: [generate_dataset, measures_dataset_2016, measures_dataset_2017, measures_dataset_2018, measures_dataset_2019, measures_dataset_2020, measures_dataset_2021, measures_dataset_2022, measures_dataset_2023, measures_dataset_2024]
outputs:
moderately_sensitive:
log1: logs/descriptive_tables.log
figure1: output/figures/incidence_*.svg
figure2: output/figures/prevalence_*.svg
figure3: output/figures/inc_comp_*.svg
figure4: output/figures/prev_comp_*.svg
figure5: output/figures/inc_adj_*.svg
figure6: output/figures/inc_ma_sex_*.svg
figure7: output/figures/prev_adj_*.svg
figure8: output/figures/inc_adj_ma_*.svg
figure9: output/figures/inc_adj_ma2_*.svg
figure10: output/figures/adj_ma_sex_*.svg
figure11: output/figures/adj_ma_sex2_*.svg
figure12: output/figures/adj_ma_age_*.svg
data1: output/data/arima_nonstandardised.csv
run_sarima:
run: r:latest analysis/200_sarima.R
needs: [run_incidence_graphs]
outputs:
moderately_sensitive:
log1: logs/sarima_log.txt
figure1: output/figures/observed_*.svg
figure2: output/figures/raw_pre_covid_*.svg
figure3: output/figures/differenced_pre_covid_*.svg
figure4: output/figures/seasonal_pre_covid_*.svg
figure5: output/figures/raw_acf_*.svg
figure6: output/figures/differenced_acf_*.svg
figure7: output/figures/seasonal_acf_*.svg
figure8: output/figures/auto_residuals_*.svg
figure9: output/figures/obs_pred_*.svg
table1: output/tables/change_incidence_byyear.csv
table2: output/tables/values_*.csv
Timeline
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Created:
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Started:
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Finished:
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Runtime: 43:25:57
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Job information
- Status
-
Succeeded
- Backend
- TPP
- Workspace
- incidence_longtermconditions
- Requested by
- Mark Russell
- Branch
- main
- Force run dependencies
- Yes
- Git commit hash
- 78babeb
- Requested actions
-
-
run_all
-
Code comparison
Compare the code used in this Job Request