yamaa 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: Would a real study need this derivation, specified this way? Does it follow CDISC ADaM: variable names, controlled terms, record structure? Flag any rule that is ambiguous or that a sponsor would handle differently.
- Inputs: Do they look like data collected in a real trial, and do they include the situations you would expect to meet in one?
- Expected output: Would independent QC programming reproduce every value from these inputs and rules?
The other tabs beside Comments are background for assessment, not under review.
Summary
EditUnder reviewWhat this benchmark meansREADME.mdGoal: one Analysis Dataset for Adverse Events (ADAE) row per
serious adverse event (AE), carrying AEDECOD and AESER.
Input: collected adverse events with study, subject, and
sequence (STUDYID, USUBJID, AESEQ), the dictionary term
(AEDECOD), and whether the event was serious (AESER).
Variables:
AEDECODis the dictionary term collected for the event.AESERisYon every row, because only serious events are kept.
Note: rows follow the order in which the events were
collected, so the serious events of one subject stay interleaved
with the serious events of other subjects exactly as collected. A
non-serious event -- or one whose seriousness was never recorded
(blank AESER) -- leaves no row.
Inputs
Under review1 source fileinput/ae.csv
Edit9 rows| STUDYID | USUBJID | AESEQ | AEDECOD | AESER |
|---|---|---|---|---|
| YAMAA-01 | 1 | HEADACHE | Y | |
| YAMAA-01 | 2 | COUGH | N | |
| YAMAA-01 | 3 | NAUSEA | Y | |
| YAMAA-01 | 1 | DIZZINESS | N | |
| YAMAA-01 | 2 | FEVER | Y | |
| YAMAA-01 | 1 | BACK PAIN | N | |
| YAMAA-01 | 2 | INFLUENZA | N | |
| YAMAA-01 | 1 | CHEST PAIN | Y | |
| YAMAA-01 | 1 | RUNNY NOSE | — |
Expected output
Under review4 expected rowsexpected/adae.csv
Edit4 rows| STUDYID | USUBJID | AESEQ | AEDECOD | AESER |
|---|---|---|---|---|
| YAMAA-01 | 1 | HEADACHE | Y | |
| YAMAA-01 | 3 | NAUSEA | Y | |
| YAMAA-01 | 2 | FEVER | Y | |
| YAMAA-01 | 1 | CHEST PAIN | Y |
Comments and assessment materials
| Dataset Name | Variable Name | Variable Label | Type | Codelist/Controlled Terms | Core | Computational Method | Origin |
|---|---|---|---|---|---|---|---|
| ADAE | STUDYID | Study Identifier | character | Set per constructed row; see the Row construction sheet. | Derived | ||
| ADAE | USUBJID | Unique Subject Identifier | character | Set per constructed row; see the Row construction sheet. | Derived | ||
| ADAE | AESEQ | Sequence Number | numeric | Set per constructed row; see the Row construction sheet. | Derived | ||
| ADAE | AEDECOD | Dictionary-Derived Term | character | Set per constructed row; see the Row construction sheet. | Derived | ||
| ADAE | AESER | Serious Event | character | Set per constructed row; see the Row construction sheet. | Derived |
| Template | Include when | STUDYID | USUBJID | AESEQ | AEDECOD | AESER |
|---|---|---|---|---|---|---|
| serious | Copy STUDYID from the AE record matching on the shared output keys, where AE.AESER = 'Y', and a row with no match is an error | Copy USUBJID from the AE record matching on the shared output keys, where AE.AESER = 'Y', and a row with no match is an error | Copy AESEQ from the AE record matching on the shared output keys, where AE.AESER = 'Y', and a row with no match is an error | Copy AEDECOD from the AE record matching on the shared output keys, where AE.AESER = 'Y', and a row with no match is an error | Copy AESER from the AE record matching on the shared output keys, where AE.AESER = 'Y', and a row with no match is an error |
| Version | Date | Author | Description | Reviewer | Sign-off |
|---|---|---|---|---|---|
| 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 |
prompts/adam-adae-serious-events/full.md
Edit12 linesFollowing CDISC ADaM standards, use the provided AE dataset to create an ADAE dataset with one record per serious adverse event.
The output dataset should contain the following columns in this order: STUDYID, USUBJID, AESEQ, AEDECOD, AESER
AEDECOD is the dictionary term collected for the event. AESER is Y on every row, because only serious events are kept. A non-serious event leaves no row.
Read the source datasets from /app/input and save the completed dataset as /app/output/adae.csv.
prompts/adam-adae-serious-events/conventions.md
Edit10 linesFollowing CDISC ADaM standards, use the provided AE dataset to create an ADAE dataset with one record per serious adverse event.
The output dataset should contain the following columns in this order: STUDYID, USUBJID, AESEQ, AEDECOD, AESER
AESER is Y on every row.
Read the source datasets from /app/input and save the completed dataset as /app/output/adae.csv.
prompts/adam-adae-serious-events/brief.md
Edit8 linesFollowing CDISC ADaM standards, use the provided AE dataset to create an ADAE dataset with one record per serious adverse event.
The output dataset should contain the following columns in this order: STUDYID, USUBJID, AESEQ, AEDECOD, AESER
Read the source datasets from /app/input and save the completed dataset as /app/output/adae.csv.
run.R
Edit4 lineslibrary(yamaa)adae <- yamaa_domain("spec.yaml")$outputadaerun.py
Edit4 linesimport yamaaadae = yamaa.yamaa_domain("spec.yaml").outputadaesolutions/adam-adae-serious-events/result.R
Edit21 lines# Reference solution for the yamaa benchmark adam-adae-serious-events (R track).## Written from the benchmark's full prompt and its inputs alone, as an agent# would write it. Harbor's oracle agent runs it to check that the prompt can# be solved and that the grader scores a correct answer 1.library(dplyr, warn.conflicts = FALSE)library(readr)ae <- read_csv( "/app/input/ae.csv", col_types = cols(AESEQ = col_integer(), .default = col_character()))# Only serious events are kept; AESER is Y on every row.adae <- ae |> filter(AESER %in% "Y") |> select(STUDYID, USUBJID, AESEQ, AEDECOD, AESER)dir.create("/app/output", showWarnings = FALSE)write_csv(adae, "/app/output/adae.csv", na = "")solutions/adam-adae-serious-events/result.py
Edit21 lines# Reference solution for the yamaa benchmark adam-adae-serious-events (Python track).## Written from the benchmark's full prompt and its inputs alone, as an agent# would write it. Harbor's oracle agent runs it to check that the prompt can# be solved and that the grader scores a correct answer 1.from pathlib import Pathimport polars as plae = pl.read_csv("/app/input/ae.csv", infer_schema=False).with_columns( pl.col("AESEQ").cast(pl.Int64))# Only serious events are kept; AESER is Y on every row.adae = ae.filter(pl.col("AESER") == "Y").select( "STUDYID", "USUBJID", "AESEQ", "AEDECOD", "AESER")Path("/app/output").mkdir(exist_ok=True)adae.write_csv("/app/output/adae.csv")solutions/adam-adae-serious-events/result.sas
Edit19 lines/* opensas reference solution for the yamaa benchmark adam-adae-serious-events. Reads the benchmark inputs and derives the requested output. Execute with the existing opensas runtime: opensas /app/output/result.sas. */data ae; length STUDYID USUBJID AEDECOD AESER $1024; infile "/app/input/ae.csv" dsd dlm="," firstobs=2 truncover lrecl=32767; input STUDYID : $char1024. USUBJID : $char1024. AESEQ AEDECOD : $char1024. AESER : $char1024.;run;proc sql; create table result as select * from ae where AESER='Y';quit;proc sql; create table final as select STUDYID, USUBJID, AESEQ, AEDECOD, AESER from result;quit;proc export data=final outfile="/app/output/adae.csv" dbms=csv replace; run;
Comments
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