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Job request: 5109

Organisation:
Bennett Institute
Workspace:
vaccine-effectiveness-hospital-admissions-validation
ID:
7pi77sxccrnqryoe
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Louis Fisher 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: 10000

actions:
  # generate_study_population_descriptives:
  #   run: cohortextractor:latest generate_cohort --study-definition study_definition_descriptives
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/input_descriptives.csv

  generate_study_population:
    run: cohortextractor:latest generate_cohort --study-definition study_definition
    outputs:
      highly_sensitive:
        cohort: output/input.csv

  # generate_results:
  #   run: python:latest python analysis/generate_results.py
  #   needs: [generate_study_population, generate_study_population_descriptives]
  #   outputs:
  #     moderately_sensitive:
  #       num_patients: output/num_patients.json
  #       ae_attendance_count_dict: output/num_ae_attendances.json
  #       hosp_dict: output/emergency_hospitalisation.json
  #       ae_dict: output/ae.json
  #       any_ae_dict: output/ae_any.json
  #       all_ae_dict: output/ae_all.json
  #       discharge_csv: output/discharge_destination.csv
  #       performance_dict: output/model_performance.json
  #       sensitivity_dict: output/sensitivity.json
  #       model_csvs: output/model_*.csv

  # generate_notebook:
  #   run: jupyter:latest jupyter nbconvert /workspace/analysis/results.ipynb --execute --to html --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
  #   needs: [generate_study_population, generate_study_population_descriptives]
  #   outputs:
  #     moderately_sensitive:
  #       notebook: output/results.html

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:05:48

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

Job information

Status
Succeeded
Backend
TPP
Workspace
vaccine-effectiveness-hospital-admissions-validation
Requested by
Louis Fisher
Branch
master
Force run dependencies
No
Git commit hash
04f8f89
Requested actions
  • generate_study_population

Code comparison

Compare the code used in this Job Request