Review ask

As a clinical trial statistician or programmer, answer two short questions in Your review: the task and the inputs. Agreeing with both approves this benchmark; disagreeing with either needs a comment. Propose a fix with the Edit button on any source file, or add it to your comments.

We suggest spending no more than 5 minutes on a review. The other tabs beside Your review are background for assessment, not under review.

Summary

Lifecycle: draftEditUnder review
What this benchmark means
README.md

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

Goal: take each record's VALUE from the study's numeric_constant calculation, for the constant that KIND names.

Input: one record per identifier naming a constant: one, zero or positive infinity.

Variables:

  • KIND is the name of the constant as stored.
  • VALUE would be the constant the calculation returns.

The calculation promises a number for every kind. For positive infinity it returns infinity, which is stored as missing, as every non-finite number is, so the calculation has returned a missing value it promised it would not. The run is rejected, and no artifact is accepted.

How to fix

Decide whether a missing result is acceptable for this calculation. If it is, say so in its function file, as schema-non-finite does, and add a test for each kind that returns one:

returns: float
may_return_missing: true

If it is not, correct the stored kind so that it names a finite constant.

Expected failure

Edit
the run is rejected; no artifact is accepted
expected/error.yaml
phase
derivation
condition
invalid_function_result
rule
FUNC-9
expected/error.yaml
phase: derivation
condition: invalid_function_result
spec_paths:
  - columns.VALUE.derivation.function
rule: FUNC-9
context:
  function: numeric_constant

Inputs

Under review
1 source file

input/source.csv

Edit
3 rows
input/source.csv
IDKIND
01one
02zero
03positive-infinity

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

Variable NameVariable LabelTypeLengthControlled Terms or FormatOriginCoreConversion DefinitionVariable TypeVariable OrderComments for Define
IDIdentifierCharCollectedCopy value from SOURCE.ID.SDTM1
KINDConstant KindCharCollectedCopy value from SOURCE.KIND.SDTM2
VALUEProject Function ResultNumDerivedCall project function numeric_constant with kind = KIND.SDTM3
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