| # Cohort data and task execution |
|
|
| The metadata package supports inspection and scoring of reporting decisions. |
| Executing a frozen task requires its prepared cohort files. Obtain source |
| cohort data through the relevant provider or study team under their access |
| terms. The CC BY 4.0 license covers this package's metadata and documentation. |
|
|
| ## Source cohorts |
|
|
| The task inventory names ABIDE1, ABIDE2, ADHD200, ABCD, ADNI, ADNI_fMRI, |
| BSNIP2, COBRE, ChineseSZ, FBIRN, GSP, HCP, HCP_Aging, JH, NACC, OASIS3, |
| OASIS3_fMRI, UKB, and OpenNeuro ds000030. It also includes constructed stress |
| datasets and evidence partitions derived from those sources. |
| |
| Use `dataset_id` in `tasks.jsonl` and `provenance` in `cases.jsonl` to identify |
| the source of each task. The metadata contains no participant tables, |
| participant-level control assignments, or preprocessing outputs. |
|
|
| ## Exact benchmark inputs |
|
|
| Each task names its discovery and replication cohorts. Store their prepared |
| tables as `<cohort>.parquet`. The runner verifies the file bytes against the |
| published SHA-256 hashes before computing results. |
|
|
| | Task type | Required prepared files | Hash field | |
| |---|---|---| |
| | Task with no `generator_spec`, including fixed stress datasets | Named discovery and replication cohorts | `tasks.jsonl`: `partition_hashes` | |
| | Task with a `generator_spec`, including random-label controls | Frozen generated discovery and replication cohorts | `outcomes.jsonl`: `generated_cohort_hashes` | |
|
|
| Place all cohorts for a task together in one directory and pass that |
| directory as `--data-root`. Additional `--data-root` arguments search other |
| directories. Generator specifications record the construction rules, seeds, |
| and assignment hashes; executing these tasks requires the generated tables. |
|
|
| Exact reruns require the original prepared artifacts, including partition |
| membership and file serialization. Raw provider downloads require further |
| preparation and do not supply those frozen files. Missing or mismatched |
| inputs produce explicit error rows. The scorer counts errors as withheld |
| and reports them separately in its coverage counts. |
|
|
| ## Analyze newly prepared data |
|
|
| Use `confirm run` with a new analysis plan for newly prepared cohorts. |
| Prepare one Parquet table per cohort with these columns: |
|
|
| | Column | Content | |
| |---|---| |
| | `subject_id` | Participant identifier | |
| | `cohort` | Cohort name matching the filename | |
| | `site` | Acquisition site or scanner batch | |
| | `age` | Numeric age | |
| | `sex` | `M` or `F` | |
| | Imaging measurements | Numeric columns with `smri_`, `pet_`, `fc_`, or `raw_` prefixes | |
|
|
| Include all additional variables named in the plan, such as `eTIV`, |
| diagnosis, or behavioral scores. Keep discovery, replication, and holdout |
| participants separate. `confirm demo --out outputs/demo` creates complete |
| synthetic tables and plans illustrating this format. The CONFIRM source |
| package also includes a CSV mapping template and conversion guide. |
|
|
| Report analyses of new cohorts with their own input identities and results. |
| The frozen benchmark records describe the published task inputs and outcomes. |
|
|
