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Job request: 366

Organisation:
The London School of Hygiene & Tropical Medicine
Workspace:
households
ID:
jxwlqy72shud5wrf

This page shows the technical details of what happened when the authorised researcher Thomas House requested one or more actions to be run against real patient data within a secure environment.

By cross-referencing the list of jobs with the pipeline section below, you can infer what security level the outputs were written to.

The output security levels are:

  • highly_sensitive
    • Researchers can never directly view these outputs
    • Researchers can only request code is run against them
  • moderately_sensitive
    • Can be viewed by an approved researcher by logging into a highly secure environment
    • These are the only outputs that can be requested for public release via a controlled output review service.

Jobs

Pipeline

Show project.yaml
version: "3.0"

expectations:
  population_size: 100000

actions:
  generate_cohort:
    run: cohortextractor:latest generate_cohort
    outputs:
      highly_sensitive:
        cohort: output/input.csv

  prepare_data:
    run: stata-mp:latest analysis/01_hh_cr_analysis_dataset.do
    needs: [generate_cohort]
    outputs:
      highly_sensitive:
        allvars: output/hh_analysis_dataset.dta

  output_descriptive:
    run: stata-mp:latest analysis/02_hh_an_caseFreq_descriptive_plots.do
    needs: [prepare_data]
    outputs:
      moderately_sensitive:
        graph1: released_outputs/an_caseFreq_descr_overall_HH_Histogram.svg
        graph2: released_outputs/an_caseFreq_descr_overall_HH_HistogramOverlay.svg
        log1: released_outputs/02_hh_an_caseFreq_descriptive_plots.log
        log2: released_outputs/an_caseDescrTable.txt


  generate_model_data:
    run: python:latest python analysis/generate_model_data.py
    needs: [prepare_data]
    outputs:
      moderately_sensitive:
        log: generate_model_data.log
        timeseries: output/case_series.pickle
        agecats: output/age_categories_series.pickle

  run_model_20_1_1:
    run: python:latest python analysis/opensafely_age_hh_th.py --starting-parameter 1 --add-ridge 20.1
    needs: [generate_model_data]
    outputs:
      moderately_sensitive:
        log: opensafely_age_hh_ridge_20_1_and_seed_1.log


  run_model_20_1_3:
    run: python:latest python analysis/opensafely_age_hh_th.py --starting-parameter 3 --add-ridge 20.1
    needs: [generate_model_data]
    outputs:
      moderately_sensitive:
        log: opensafely_age_hh_ridge_20_1_and_seed_3.log


  run_model_20_1_5:
    run: python:latest python analysis/opensafely_age_hh_th.py --starting-parameter 5 --add-ridge 20.1
    needs: [generate_model_data]
    outputs:
      moderately_sensitive:
        log: opensafely_age_hh_ridge_20_1_and_seed_5.log


  run_model_20_1_81:
    run: python:latest python analysis/opensafely_age_hh_th.py --starting-parameter 81 --add-ridge 20.1
    needs: [generate_model_data]
    outputs:
      moderately_sensitive:
        log: opensafely_age_hh_ridge_20_1_and_seed_81.log


  run_model_20_1_83:
    run: python:latest python analysis/opensafely_age_hh_th.py --starting-parameter 83 --add-ridge 20.1
    needs: [generate_model_data]
    outputs:
      moderately_sensitive:
        log: opensafely_age_hh_ridge_20_1_and_seed_83.log


  run_model_20_1_85:
    run: python:latest python analysis/opensafely_age_hh_th.py --starting-parameter 85 --add-ridge 20.1
    needs: [generate_model_data]
    outputs:
      moderately_sensitive:
        log: opensafely_age_hh_ridge_20_1_and_seed_85.log


  run_model_20_1_23:
    run: python:latest python analysis/opensafely_age_hh_th.py --starting-parameter 23 --add-ridge 20.1
    needs: [generate_model_data]
    outputs:
      moderately_sensitive:
        log: opensafely_age_hh_ridge_20_1_and_seed_23.log


  run_model_20_1_37:
    run: python:latest python analysis/opensafely_age_hh_th.py --starting-parameter 37 --add-ridge 20.1
    needs: [generate_model_data]
    outputs:
      moderately_sensitive:
        log: opensafely_age_hh_ridge_20_1_and_seed_37.log


  run_model_20_1_42:
    run: python:latest python analysis/opensafely_age_hh_th.py --starting-parameter 42 --add-ridge 20.1
    needs: [generate_model_data]
    outputs:
      moderately_sensitive:
        log: opensafely_age_hh_ridge_20_1_and_seed_42.log


  run_model_20_1_13:
    run: python:latest python analysis/opensafely_age_hh_th.py --starting-parameter 13 --add-ridge 20.1
    needs: [generate_model_data]
    outputs:
      moderately_sensitive:
        log: opensafely_age_hh_ridge_20_1_and_seed_13.log

  run_all:
    needs:
      [run_model_20_1_1, run_model_20_1_3, run_model_20_1_5, run_model_20_1_81, run_model_20_1_83, run_model_20_1_85, run_model_20_1_23, run_model_20_1_37, run_model_20_1_42, run_model_20_1_13]
    # In order to be valid this action needs to define a run commmand and some
    # output. We don't really care what these are but the below does the trick.
    # In a future release of the platform, this special action won't need to be
    # defined at all.
    run: cohortextractor:latest --version
    outputs:
      moderately_sensitive:
        whatever: project.yaml

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:00:07

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

Job request

Status
Succeeded
Backend
TPP
Workspace
households
Requested by
Thomas House
Branch
master
Force run dependencies
No
Git commit hash
9126c8f
Requested actions
  • run_all

Code comparison

Compare the code used in this job request