Job request: 6728
- Organisation:
- University of Manchester
- Workspace:
- hosp_pred_urti_2019
- ID:
- jv3pk2ujfti36hmy
This page shows the technical details of what happened when authorised researcher ali requested one or more actions to be run against real patient data in the project, within a secure environment.
By cross-referencing the indicated Requested Actions with the
Pipeline section below, you can infer what
security level
various outputs were written to. Outputs marked as
highly_sensitive
can never be viewed directly by a researcher; 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
-
- Job identifier:
-
ee57acdfewq7amlx
Pipeline
Show project.yaml
version: '3.0'
expectations:
population_size: 1000
actions:
# generate_study_population:
# run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-01-01 to today by month" --skip-existing --output-dir=output/measures --output-format=csv.gz
# outputs:
# highly_sensitive:
# cohort: output/measures/input_*.csv.gz
generate_study_population_hospitalisation_1:
run: cohortextractor:latest generate_cohort --study-definition study_definition_hospitalisation --index-date-range "2019-01-01 to 2019-03-01 by month" --output-dir=output/hospitalisation_data --output-format=csv.gz
outputs:
highly_sensitive:
cohort: output/hospitalisation_data/input_hospitalisation_*.csv.gz
generate_study_population_hospitalisation_2:
run: cohortextractor:latest generate_cohort --study-definition study_definition_hospitalisation --index-date-range "2019-04-01 to 2019-06-01 by month" --output-dir=output/hospitalisation_data --output-format=csv.gz
outputs:
highly_sensitive:
cohort: output/hospitalisation_data/input_hospitalisatio*.csv.gz
generate_study_population_hospitalisation_3:
run: cohortextractor:latest generate_cohort --study-definition study_definition_hospitalisation --index-date-range "2019-07-01 to 2019-09-01 by month" --output-dir=output/hospitalisation_data --output-format=csv.gz
outputs:
highly_sensitive:
cohort: output/hospitalisation_data/input_hospitalisati*.csv.gz
generate_study_population_hospitalisation_4:
run: cohortextractor:latest generate_cohort --study-definition study_definition_hospitalisation --index-date-range "2019-10-01 to 2019-12-01 by month" --output-dir=output/hospitalisation_data --output-format=csv.gz
outputs:
highly_sensitive:
cohort: output/hospitalisation_data/input_hospitalisat*.csv.gz
# generate_measures:
# run: cohortextractor:latest generate_measures --study-definition study_definition --skip-existing --output-dir=output/measures
# needs: [generate_study_population]
# outputs:
# moderately_sensitive:
# measure_csv: output/measures/measure_*.csv
#generate_notebook_starpu:
# run: jupyter:latest jupyter nbconvert /workspace/analysis/starpu.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_risk --ExecutePreprocessor.timeout=86400
# needs: [generate_measures]
# outputs:
# moderately_sensitive:
# notebook: output/hospitalisation_risk/starpu.html
# figures: output/hospitalisation_risk/*
#tables: output/tables/*
#csvs: output/*/* # two possible subfolders
#text: output/text/*
# generate_notebook_hospitalisation_analysis:
# run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_analysis.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_risk --ExecutePreprocessor.timeout=86400
# needs: [generate_study_population_hospitalisation]
# outputs:
# moderately_sensitive:
# notebook: output/hospitalisation_risk/hospitalisation_analysis.html
# figures: output/hospitalisation_risk/*
# generate_notebook_hospitalisation_prediction_uti:
# run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_prediction_uti.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_prediction_uti --ExecutePreprocessor.timeout=86400
# needs: [generate_study_population_hospitalisation]
# outputs:
# moderately_sensitive:
# notebook: output/hospitalisation_prediction_uti/hospitalisation_prediction_uti.html
# figures: output/hospitalisation_prediction_uti/*
generate_notebook_hospitalisation_prediction_urti:
run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_prediction_urti.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_prediction_urti --ExecutePreprocessor.timeout=86400
needs: [generate_study_population_hospitalisation_1, generate_study_population_hospitalisation_2, generate_study_population_hospitalisation_3, generate_study_population_hospitalisation_4]
# , generate_study_population_hospitalisation_3, generate_study_population_hospitalisation_4]
outputs:
moderately_sensitive:
notebook: output/hospitalisation_prediction_urti/hospitalisation_prediction_urti.html
figures: output/hospitalisation_prediction_urti/*
# generate_notebook_hospitalisation_prediction:
# run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_prediction.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_prediction --ExecutePreprocessor.timeout=86400
# needs: [generate_study_population_hospitalisation]
# outputs:
# moderately_sensitive:
# notebook: output/hospitalisation_prediction/hospitalisation_prediction.html
# figures: output/hospitalisation_prediction/*
Timeline
-
Created:
-
Started:
-
Finished:
-
Runtime: 01:03:37
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Job information
- Status
-
Failed
- Backend
- TPP
- Workspace
- hosp_pred_urti_2019
- Requested by
- ali
- Branch
- hospitalisation
- Force run dependencies
- No
- Git commit hash
- 5a05e68
- Requested actions
-
-
generate_notebook_hospitalisation_prediction_urti
-
Code comparison
Compare the code used in this Job Request