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Summary
EditUnder reviewWhat this benchmark meansREADME.mdPublic entries: Python and R. Passing coverage requires an installed inventory.
Goal: 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 |
Human review and assessment
| 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 no match yields blank | Copy USUBJID from the AE record matching on the shared output keys, where AE.AESER = 'Y', and no match yields blank | Copy AESEQ from the AE record matching on the shared output keys, where AE.AESER = 'Y', and no match yields blank | Copy AEDECOD from the AE record matching on the shared output keys, where AE.AESER = 'Y', and no match yields blank | Copy AESER from the AE record matching on the shared output keys, where AE.AESER = 'Y', and no match yields blank |
| Version | Date | Author | Description | Reviewer | Sign-off |
|---|---|---|---|---|---|
| 1.7 | 2026-10-20 | yamaa docs build | Read 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 | ||
| 1.6 | 2026-10-17 | yamaa docs build | Describe collected date parts written as ISO 8601 date text and times of day counted in seconds since midnight | ||
| 1.5 | 2026-10-17 | yamaa docs build | Name 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 | ||
| 1.4 | 2026-10-15 | yamaa docs build | State datetime precision codes through the hour and minute, and complete only the time parts a collected datetime lacks | ||
| 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
Edit16 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
Keep only the events recorded as serious, those with AESER "Y". A non-serious event, or an event whose seriousness was never recorded (AESER has no value), leaves no row. AEDECOD is the dictionary term collected for the event. AESER is "Y" on every row, because only serious events are kept. 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.
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.
R
Edit3 lineslibrary(yamaa)yamaa_spec("spec.yaml")$run()$outputPython
Edit3 linesimport yamaayamaa.spec("spec.yaml").run().outputsolutions/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
Edit37 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."""Create ADAE: one record per serious adverse event (AESER == "Y").Reads AE from /app/input/ae.csv and writes the serious events, in theorder collected, to /app/output/adae.csv with columnsSTUDYID, USUBJID, AESEQ, AEDECOD, AESER."""import csvimport osINPUT_PATH = "/app/input/ae.csv"OUTPUT_PATH = "/app/output/adae.csv"COLUMNS = ["STUDYID", "USUBJID", "AESEQ", "AEDECOD", "AESER"]def main(): with open(INPUT_PATH, newline="", encoding="utf-8") as f: rows = list(csv.DictReader(f)) serious = [row for row in rows if (row.get("AESER") or "") == "Y"] os.makedirs(os.path.dirname(OUTPUT_PATH), exist_ok=True) with open(OUTPUT_PATH, "w", newline="", encoding="utf-8") as f: writer = csv.DictWriter(f, fieldnames=COLUMNS) writer.writeheader() for row in serious: writer.writerow({col: row.get(col, "") for col in COLUMNS})if __name__ == "__main__": main()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;