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Job request: 9112

Organisation:
University of Manchester
Workspace:
hospitalisation_pred
ID:
7hgiw3jb3wlu5apj
View repo View project.yaml

This page shows the technical details of what happened when the 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 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

Pipeline

Show project.yaml 
version: '3.0'

expectations:
  population_size: 200000

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:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_hospitalisation --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/hospitalisation_data/input_hospitalisation.csv.gz

  # generate_study_population_bmi:
  #   run: cohortextractor:latest generate_cohort --study-definition study_definition_bmi --output-format=csv.gz
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/hospitalisation_data/input_bmi.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_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_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,generate_study_population_bmi]
    needs: [generate_study_population_hospitalisation]
    outputs:
      moderately_sensitive:
        notebook: output/hospitalisation_prediction_urti/hospitalisation_prediction_urti.html 
        figures: output/hospitalisation_prediction_urti/*


  # generate_notebook_hospitalisation_prediction_urti_lr:
  #   run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_prediction_urti_lr.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_prediction_urti --ExecutePreprocessor.timeout=86400
  #   needs: [generate_study_population_hospitalisation]
  #   outputs:
  #     moderately_sensitive:
  #       notebook: output/hospitalisation_prediction_urti/hospitalisation_prediction_urti_lr.html 
  #       figures: output/hospitalisation_prediction_urti/*

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 10:57:30

These timestamps are generated and stored using the UTC timezone on the TPP backend.

Job information

Status
Failed
Backend
TPP
Workspace
hospitalisation_pred
Requested by
ali
Branch
hosp_pred
Force run dependencies
Yes
Git commit hash
ef37445
Requested actions
  • generate_study_population_hospitalisation
  • generate_notebook_hospitalisation_prediction_urti

Code comparison

Compare the code used in this Job Request