Reject Ambiguous Type

Review ask

As a clinical trial statistician or programmer, challenge anything in this benchmark: describe a problem in Comments, or propose a fix with the Edit button on any source file.

Task: Is this a specification error a study team could realistically make, and should the build stop on it rather than continue?
Inputs: Do they trigger the failure for the reason the summary gives?
Expected failure: Is this the right error, raised at the right point, and would it tell the programmer what to fix?

The other tabs beside Comments are background for assessment, not under review.

Summary

EditUnder reviewWhat this benchmark means

README.md

Goal: attempt one laboratory analysis record per collected laboratory result, carrying AVAL for the numeric analysis value.

Input: collected laboratory results with the result in standard units (LBSTRESN).

Variables:

AVAL would be the numeric analysis value, copying LBSTRESN. Whole and fractional numbers are stored as different kinds of value, but the declared kind says only number. Choosing either representation would invent a precision decision the declaration did not make, so the run is rejected before any data is read and no artifact is accepted.

How to fix

Choose the type from the measurement contract. Use int only when fractions are impossible; otherwise use float:

- name: AVAL
  type: float
  label: Analysis Value
  derivation: LB.LBSTRESN

The allowed column types are str, int, float, date, and datetime.

Expected failure

Editthe run is rejected; no artifact is accepted

expected/error.yaml

phase: validation
condition: value_not_permitted
requirement: REQ-0012

expected/error.yaml

phase: validation
condition: value_not_permitted
spec_paths:
  - columns.AVAL.type
requirement: REQ-0012
context:
  value: number
  permitted: [str, int, float, date, datetime]

YAML specification

1 spec file

spec.yaml

Edit30 lines

1schema_version: "1.0"2domain: ADLB3keys: [STUDYID, USUBJID, LBSEQ]4input:5  LB: {path: input/lb.csv, types: {LBSEQ: int, LBSTRESN: float}}67output:8  path: adlb.csv9  columns: [STUDYID, USUBJID, LBSEQ, AVAL]1011columns:12  - name: STUDYID13    type: str14    label: Study Identifier15    derivation: LB.STUDYID1617  - name: USUBJID18    type: str19    label: Unique Subject Identifier20    derivation: LB.USUBJID2122  - name: LBSEQ23    type: int24    label: Sequence Number25    derivation: LB.LBSEQ2627  - name: AVAL28    type: number29    label: Analysis Value30    derivation: LB.LBSTRESN

Inputs

Under review1 source file

input/lb.csv

Edit1 row

input/lb.csv
STUDYID	USUBJID	LBSEQ	LBSTRESN
PILOT7		1	12.5

Unexpected Output

Under reviewNo artifact is produced

No fixture files in this directory.

Shaded columns are derived— = missing value

Comments and assessment materials

Dataset Name	Variable Name	Variable Label	Type	Computational Method	Origin
ADLB	STUDYID	Study Identifier	character	Copy value from LB.STUDYID.	Predecessor
ADLB	USUBJID	Unique Subject Identifier	character	Copy value from LB.USUBJID.	Predecessor
ADLB	LBSEQ	Sequence Number	numeric	Copy value from LB.LBSEQ.	Predecessor
ADLB	AVAL	Analysis Value	number	Copy value from LB.LBSTRESN.	Predecessor

Version	Date	Author	Description
1.3	2026-09-29	yamaa docs build	Show study codelist names, external dictionaries, and ISO 8601 formats in variable rows; list the document's codelist values and metadata
1.2	2026-09-29	yamaa docs build	Classify ADaM copies from a declared input as Predecessor and recodes as Derived, and SDTM recodes of locally derived columns as Derived
1.1	2026-09-29	yamaa docs build	Resolve lookups into the donor record they select, and give every derivation shape a plain-language rule instead of its raw YAML
1.0		yamaa docs build	Initial generation from spec.yaml

How to fix

input/lb.csv

Comments

Mapping spec