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Summary

Lifecycle: draftEditUnder review
What this benchmark means
README.md

Public entries: Python and R. Passing coverage requires an installed inventory.

Goal: give every adverse event record its subject's age (AGE), sex (SEX) and baseline weight (WEIGHTBL) from the subject-level analysis dataset (ADSL).

Input: adverse event records carrying the reported term (AETERM), and the ADSL that the study's subject-level specification builds from collected demographics, which records age and sex but no weight.

Variables:

  • AGE and SEX would be the subject's values in ADSL, repeated on each of their events.
  • WEIGHTBL would be the subject's baseline weight, which ADSL does not record.

Note: a variable taken from ADSL keeps the name, type and label ADSL gives it, so it must be one ADSL publishes. The run is refused before any record is read instead of inventing a variable ADSL does not have.

How to fix

Decide where baseline weight comes from. When the subject-level dataset should carry it, add WEIGHTBL to ADSL first; the copy entry can then list it. Otherwise leave it out of the copy entry and of output.columns, or derive it in this dataset from a source that records it:

  - copy:
      dataset: ADSL
      columns: [AGE, SEX]

Expected failure

Edit
the run is rejected; no artifact is accepted
expected/error.yaml
phase
validation
condition
unknown_field
rule
SPEC-9
expected/error.yaml
phase: validation
condition: unknown_field
spec_paths:
  - columns[4].copy.columns[2]
rule: SPEC-9
context:
  identifier: ADSL.WEIGHTBL

Inputs

Under review
2 source files

input/ae.csv

Edit
2 rows
input/ae.csv
STUDYIDUSUBJIDAESEQAETERM
YAMAA-011HEADACHE
YAMAA-011NAUSEA

input/dm.csv

Edit
2 rows
input/dm.csv
STUDYIDUSUBJIDAGESEX
YAMAA-0164F
YAMAA-0147M

Unexpected Output

Under review
No artifact is produced

No fixture files in this directory.

Shaded columns are derived— = missing value

Human review and assessment

Your review

2 questions and your comments · View benchmark discussions

Mapping spec

Generated from the benchmark YAML; do not edit by hand

Dataset NameVariable NameVariable LabelTypeCodelist/Controlled TermsCoreComputational MethodOrigin
ADAESTUDYIDStudy IdentifiercharacterCopy value from AE.STUDYID.Predecessor
ADAEUSUBJIDUnique Subject IdentifiercharacterCopy value from AE.USUBJID.Predecessor
ADAEAESEQSequence NumbernumericCopy value from AE.AESEQ.Predecessor
ADAEAETERMReported Term for the Adverse EventcharacterCopy value from AE.AETERM.Predecessor
VersionDateAuthorDescriptionReviewerSign-off
1.72026-10-20yamaa docs buildRead a specification in the 1.0 surface as its 0.5 counterpart; state that missing values stay missing where a mapping declares no missing handler, and leave out a declared missing answer that restates a handler's default
1.62026-10-17yamaa docs buildDescribe collected date parts written as ISO 8601 date text and times of day counted in seconds since midnight
1.52026-10-17yamaa docs buildName collected precision in words instead of letter codes; state imputation fallbacks, minimum source precision, bounds ignored outside the collected period, and invalid text with no handler as an error; describe date and datetime shifts, imputation flag codes, and partial text giving no date part
1.42026-10-15yamaa docs buildState datetime precision codes through the hour and minute, and complete only the time parts a collected datetime lacks
1.32026-09-29yamaa docs buildShow study codelist names, external dictionaries, and ISO 8601 formats in variable rows; list the document's codelist values and metadata
1.22026-09-29yamaa docs buildClassify ADaM copies from a declared input as Predecessor and recodes as Derived, and SDTM recodes of locally derived columns as Derived
1.12026-09-29yamaa docs buildResolve lookups into the donor record they select, and give every derivation shape a plain-language rule instead of its raw YAML
1.0yamaa docs buildInitial generation from spec.yaml