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This page shows the technical details of what happened when authorised researcher George Hickman requested one or more actions to be run against real patient data in the Carehomes 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
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.
Show Hide project.yaml
version: '3.0' expectations: population_size: 1000000 actions: generate_cohort: run: cohortextractor:latest generate_cohort --study-definition study_definition outputs: highly_sensitive: cohort: input.csv generate_cohort_coverage: run: cohortextractor:latest generate_cohort --study-definition study_definition_coverage outputs: highly_sensitive: cohort: input_coverage.csv calc_coverage: run: r:latest analysis/calculate_tpp_coverage.R input_coverage.csv data/msoa_pop.csv needs: [generate_cohort_coverage] outputs: moderately_sensitive: log: coverage_log.txt rds: tpp_msoa_coverage.rds csv: tpp_msoa_coverage.csv figure: total_vs_tpp_pop.png # map: map_coverage_msoa.pdf data_check: run: r:latest analysis/data_check.R input.csv tpp_msoa_coverage.rds needs: [generate_cohort, calc_coverage] outputs: moderately_sensitive: log: data_checks.txt figure1: tpp_coverage_msoa.png figure2: tpp_coverage_carehomes.png data_setup: run: r:latest analysis/data_setup.R input.csv tpp_msoa_coverage.rds 90 needs: [generate_cohort, calc_coverage] outputs: moderately_sensitive: log: data_setup_log.txt rds: community_prevalence.rds csv: community_prevalence.csv highly_sensitive: analysisdata: analysisdata.rds input_clean: input_clean.rds ch_linelist: ch_linelist.rds ch_agg_long: ch_agg_long.rds descriptive: needs: [data_setup] run: r:latest analysis/descriptive.R input_clean.rds ch_linelist.rds ch_agg_long.rds community_prevalence.rds outputs: moderately_sensitive: report: descriptive.pdf log: log_descriptive.txt data: ch_gp_permsoa.csv run_models_50_cutoff: needs: [data_setup] run: r:latest analysis/run_models.R analysisdata.rds community_prevalence.rds 50 outputs: moderately_sensitive: coeffs: coeffs_bestmod_50.csv output: output_model_run_50.txt log: log_model_run_50.txt highly_sensitive: fit: fit_opt_50.rds data: testdata_50.rds validate_models_50_cutoff: needs: [run_models_50_cutoff] run: r:latest analysis/validate_models.R fit_opt_50.rds testdata_50.rds 50 outputs: moderately_sensitive: report: test_pred_figs_50.pdf run_models_90_cutoff: needs: [data_setup] run: r:latest analysis/run_models.R analysisdata.rds community_prevalence.rds 90 outputs: moderately_sensitive: coeffs: coeffs_bestmod_90.csv output: output_model_run_90.txt log: log_model_run_90.txt highly_sensitive: fit: fit_opt_90.rds data: testdata_90.rds validate_models_90_cutoff: needs: [run_models_90_cutoff] run: r:latest analysis/validate_models.R fit_opt_90.rds testdata_90.rds 90 outputs: moderately_sensitive: report: test_pred_figs_90.pdf run_all: needs: [validate_models_90_cutoff, validate_models_50_cutoff, descriptive] # 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 seems to # do the trick. run: cohortextractor:latest --version outputs: moderately_sensitive: whatever: project.yaml
State is inferred from the related Jobs.
Timings set to UTC timezone.
- Runtime: 00:01:18