List the adverse events each medication was given for

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Summary

EditUnder reviewWhat this benchmark means

README.md

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

Goal: carry on each concomitant medication record, named by CMTRT and identified by its sequence number CMSEQ, the adverse events it was given for: their sequence numbers (AESEQS), their distinct reported terms (AETERMS) and how many distinct terms there are (AETERMN).

Input: collected concomitant medications (CM), adverse events (AE) and related records (RELREC), which tie a medication to the adverse events it was given for through a shared relationship identifier.

Variables:

In RELAE, one record per adverse event a relationship names: RELID is the relationship, and AETERM the event's reported term, read from the subject's adverse event record with that sequence number (AESEQ).
AESEQS lists the sequence numbers of the medication's related adverse events in increasing numeric order, separated by a comma and a space; blank when the medication is related to no adverse event.
AETERMS lists the reported terms of those events in alphabetical order, each term once, separated by a comma and a space; blank when there is none.
AETERMN is the number of different terms AETERMS lists; blank, not zero, when the medication is related to no adverse event.

Note: a relationship may also tie the medication to records other than adverse events, such as medical history, and no list includes those. Sequence numbers sort as numbers, so 2 comes before 10.

YAML specification

2 spec files

spec_relae.yaml
Edit57 lines
1yamaa: "1.0"2type: spec3model: ADaM4domain: RELAE5keys: [STUDYID, USUBJID, RELID, AESEQ]67input:8  RELREC: input/relrec.csv9  AE:10    path: input/ae.csv11    types:12      AESEQ: int1314# One record per adverse event a relationship names. Records that tie the15# relationship to a medication or to medical history are not events.16base: RELREC17filter: "RELREC.RDOMAIN = 'AE' AND RELREC.IDVAR = 'AESEQ'"1819output:20  path: relae.csv21  columns: [STUDYID, USUBJID, RELID, AESEQ, AETERM]22  order_by: [STUDYID, USUBJID, RELID, AESEQ]2324# A relationship that names an adverse event the AE domain does not hold25# is a data error, not a blank term.26intermediates:27  - id: AEREC28    dataset: AE29    key: {STUDYID: STUDYID, USUBJID: USUBJID, AESEQ: AESEQ}30    require_match: true3132columns:33  - name: STUDYID34    type: str35    label: Study Identifier36    derivation: RELREC.STUDYID3738  - name: USUBJID39    type: str40    label: Unique Subject Identifier41    derivation: RELREC.USUBJID4243  - name: RELID44    type: str45    label: Relationship Identifier46    derivation: RELREC.RELID4748  # RELREC holds the sequence number as text; the column makes it a number.49  - name: AESEQ50    type: int51    label: Sequence Number52    derivation: RELREC.IDVARVAL5354  - name: AETERM55    type: str56    label: Reported Term for the Adverse Event57    derivation: AEREC.AETERM
spec_adcm.yaml
Edit96 lines
1yamaa: "1.0"2type: spec3model: ADaM4domain: ADCM5keys: [STUDYID, USUBJID, CMSEQ]67input:8  CM: input/cm.csv9  RELREC: input/relrec.csv10  # RELAE is the artifact spec_relae.yaml saves before this entry is built:11  # each adverse event a relationship names, with its reported term.12  RELAE:13    path: relae.csv14    schema: spec_relae.yaml15base: CM1617output:18  path: adcm.csv19  columns: [STUDYID, USUBJID, CMSEQ, CMTRT, AESEQS, AETERMS, AETERMN]20  order_by: [STUDYID, USUBJID, CMSEQ]2122# The relationship the medication record belongs to, found through its own23# RELREC record. A medication in two relationships has no one answer and24# fails the run.25intermediates:26  - id: CMREL27    dataset: RELREC28    key: {STUDYID: STUDYID, USUBJID: USUBJID, IDVARVAL: CMSEQTXT}29    filter: "RELREC.RDOMAIN = 'CM' AND RELREC.IDVAR = 'CMSEQ'"3031columns:32  - name: STUDYID33    type: str34    label: Study Identifier35    derivation: CM.STUDYID3637  - name: USUBJID38    type: str39    label: Unique Subject Identifier40    derivation: CM.USUBJID4142  - name: CMSEQ43    type: int44    label: Sequence Number45    derivation: CM.CMSEQ4647  - name: CMTRT48    type: str49    label: Reported Name of Drug, Med, or Therapy50    derivation: CM.CMTRT5152  # RELREC names the medication record by its sequence number as text.53  - name: CMSEQTXT54    type: str55    label: Sequence Number as Text56    derivation: CM.CMSEQ5758  - name: RELID59    type: str60    label: Relationship Identifier61    derivation: CMREL.RELID6263  # The related sequence numbers are text in RELREC, where 10 sorts before64  # 2; each becomes a number first, so the list is in numeric order.65  - name: AESEQS66    type: str67    label: Related Adverse Event Sequence Numbers68    derivation:69      aggregate:70        key: {STUDYID: STUDYID, USUBJID: USUBJID, RELID: RELID}71        filter: "RELREC.RDOMAIN = 'AE' AND RELREC.IDVAR = 'AESEQ'"72        derivations:73          SEQN: {type: int, derivation: RELREC.IDVARVAL}74        order_by: [SEQN]75        separator: ", "76        expr: "STR_JOIN(SEQN)"7778  - name: AETERMS79    type: str80    label: Related Adverse Event Terms81    derivation:82      aggregate:83        key: {STUDYID: STUDYID, USUBJID: USUBJID, RELID: RELID}84        order_by: [RELAE.AETERM]85        separator: ", "86        distinct: true87        expr: "STR_JOIN(RELAE.AETERM)"8889  - name: AETERMN90    type: int91    label: Number of Distinct Related Adverse Event Terms92    derivation:93      aggregate:94        key: {STUDYID: STUDYID, USUBJID: USUBJID, RELID: RELID}95        distinct: true96        expr: "COUNT(RELAE.AETERM)"

Inputs

Under review3 source files

input/ae.csv

Edit6 rows

input/ae.csv
STUDYID	AESEQ	AETERM
YAMAA-01	1	NAUSEA
YAMAA-01	2	HEADACHE
YAMAA-01	3	BACK PAIN
YAMAA-01	10	HEADACHE
YAMAA-01	1	HEADACHE
YAMAA-01	4	FEVER

input/cm.csv

Edit4 rows

input/cm.csv
STUDYID	CMSEQ	CMTRT
YAMAA-01	1	PARACETAMOL
YAMAA-01	2	IBUPROFEN
YAMAA-01	3	LORATADINE
YAMAA-01	1	PARACETAMOL

input/relrec.csv

Edit9 rows

input/relrec.csv
STUDYID	RDOMAIN	IDVAR	IDVARVAL	RELTYPE	RELID
YAMAA-01	CM	CMSEQ	1	—	1
YAMAA-01	AE	AESEQ	10	—	1
YAMAA-01	AE	AESEQ	2	—	1
YAMAA-01	CM	CMSEQ	2	—	2
YAMAA-01	AE	AESEQ	3	—	2
YAMAA-01	MH	MHSEQ	1	—	2
YAMAA-01	CM	CMSEQ	1	—	1
YAMAA-01	AE	AESEQ	4	—	1
YAMAA-01	AE	AESEQ	1	—	1

Expected output

Under review9 expected rows

expected/adcm.csv

Edit4 rows

expected/adcm.csv
STUDYID	CMSEQ	CMTRT	AESEQS	AETERMS	AETERMN
YAMAA-01	1	PARACETAMOL	2, 10	HEADACHE	1
YAMAA-01	2	IBUPROFEN	3	BACK PAIN	1
YAMAA-01	3	LORATADINE	—	—	—
YAMAA-01	1	PARACETAMOL	1, 4	FEVER, HEADACHE	2

expected/relae.csv

Edit5 rows

expected/relae.csv
STUDYID	RELID	AESEQ	AETERM
YAMAA-01	1	2	HEADACHE
YAMAA-01	1	10	HEADACHE
YAMAA-01	2	3	BACK PAIN
YAMAA-01	1	1	HEADACHE
YAMAA-01	1	4	FEVER

Shaded columns are derived— = missing value

Human review and assessment

Dataset Name	Variable Name	Variable Label	Type	Computational Method	Origin
ADCM	STUDYID	Study Identifier	character	Copy value from CM.STUDYID.	Predecessor
ADCM	USUBJID	Unique Subject Identifier	character	Copy value from CM.USUBJID.	Predecessor
ADCM	CMSEQ	Sequence Number	numeric	Copy value from CM.CMSEQ.	Predecessor
ADCM	CMTRT	Reported Name of Drug, Med, or Therapy	character	Copy value from CM.CMTRT.	Predecessor
ADCM	AESEQS	Related Adverse Event Sequence Numbers	character	Aggregate STR_JOIN(SEQN) over records whose STUDYID equals STUDYID, USUBJID equals USUBJID and RELID equals RELID, where RELREC.RDOMAIN = 'AE' AND RELREC.IDVAR = 'AESEQ', with SEQN as RELREC.IDVARVAL.	Derived
ADCM	AETERMS	Related Adverse Event Terms	character	Aggregate STR_JOIN(RELAE.AETERM) over records whose STUDYID equals STUDYID, USUBJID equals USUBJID and RELID equals RELID.	Derived
ADCM	AETERMN	Number of Distinct Related Adverse Event Terms	numeric	Aggregate COUNT(RELAE.AETERM) over records whose STUDYID equals STUDYID, USUBJID equals USUBJID and RELID equals RELID.	Derived

Version	Date	Author	Description
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-adcm-related-events/full.md

Edit38 lines

Following CDISC ADaM standards, use the provided AE, CM, and RELREC datasets to create a RELAE dataset with one record per adverse event a relationship names and an ADCM dataset with one record per concomitant medication record.

The RELAE dataset should contain the following columns in this order: STUDYID, USUBJID, RELID, AESEQ, AETERM The ADCM dataset should contain the following columns in this order: STUDYID, USUBJID, CMSEQ, CMTRT, AESEQS, AETERMS, AETERMN

RELREC ties a medication to the adverse events it was given for through a shared relationship identifier, RELID. A relationship belongs to one subject: the same RELID in two subjects names two different relationships. A RELREC record names a medication when RDOMAIN is "CM" and IDVAR is "CMSEQ", and an adverse event when RDOMAIN is "AE" and IDVAR is "AESEQ", with the sequence number in IDVARVAL.

RELAE:

RELAE holds one record for each adverse event a relationship names, and none for a related record of any other domain, such as medical history.
RELID is the relationship, AESEQ the event's sequence number, and AETERM the reported term of the subject's adverse event record with that AESEQ.

ADCM:

A medication's related adverse events are the adverse events named by the subject's relationship that names the medication's CMSEQ; no list includes related records of other domains.
AESEQS lists the sequence numbers of the related adverse events in increasing numeric order, written as whole numbers and separated by a comma and a space (", "). Sequence numbers sort as numbers, so 2 comes before 10.
AETERMS lists the reported terms of those events in alphabetical order, each term once, separated by a comma and a space (", ").
AETERMN is the number of different terms AETERMS lists.
When a medication is related to no adverse event, AESEQS, AETERMS and AETERMN have no value; AETERMN is blank, not zero.

Read the source datasets from /app/input and save the completed RELAE dataset as /app/output/relae.csv and the completed ADCM dataset as /app/output/adcm.csv.

prompts/adam-adcm-related-events/conventions.md

Edit17 lines

AESEQS lists sequence numbers in increasing numeric order, written as whole numbers, and AETERMS lists terms in alphabetical order, each term once, both separated by a comma and a space (", "). AESEQS, AETERMS and AETERMN may have no value; AETERMN is then blank, not zero.

Read the source datasets from /app/input and save the completed RELAE dataset as /app/output/relae.csv and the completed ADCM dataset as /app/output/adcm.csv.

prompts/adam-adcm-related-events/brief.md

Edit12 lines

Read the source datasets from /app/input and save the completed RELAE dataset as /app/output/relae.csv and the completed ADCM dataset as /app/output/adcm.csv.

R

Edit4 lines

1library(yamaa)23yamaa_spec("spec_relae.yaml")$run()$save()4yamaa_spec("spec_adcm.yaml")$run()$output

Python

Edit4 lines

1import yamaa23yamaa.spec("spec_relae.yaml").run().save()4yamaa.spec("spec_adcm.yaml").run().output

solutions/adam-adcm-related-events/result.R

Edit78 lines

1# Reference solution for the yamaa benchmark adam-adcm-related-events (R track).2#3# Written from the benchmark's full prompt and its inputs alone, as an agent4# would write it. Harbor's oracle agent runs it to check that the prompt can5# be solved and that the grader scores a correct answer 1.67read_text <- function(name) {8  read.csv(9    file.path("/app/input", name),10    colClasses = "character",11    na.strings = character(0),12    check.names = FALSE13  )14}1516ae <- read_text("ae.csv")17cm <- read_text("cm.csv")18relrec <- read_text("relrec.csv")1920# Each adverse event a relationship names, with the event's reported term.21events <- relrec[relrec$RDOMAIN == "AE" & relrec$IDVAR == "AESEQ", ]22relae <- data.frame(23  STUDYID = events$STUDYID,24  USUBJID = events$USUBJID,25  RELID = events$RELID,26  AESEQ = as.integer(events$IDVARVAL),27  stringsAsFactors = FALSE28)29term_key <- paste(ae$STUDYID, ae$USUBJID, as.integer(ae$AESEQ), sep = "\r")30relae$AETERM <- ae$AETERM[match(31  paste(relae$STUDYID, relae$USUBJID, relae$AESEQ, sep = "\r"),32  term_key33)]34relae <- relae[order(relae$STUDYID, relae$USUBJID, relae$RELID, relae$AESEQ,35                     method = "radix"), ]3637# The relationship each medication belongs to.38links <- relrec[relrec$RDOMAIN == "CM" & relrec$IDVAR == "CMSEQ", ]39relid <- links$RELID[match(40  paste(cm$STUDYID, cm$USUBJID, cm$CMSEQ, sep = "\r"),41  paste(links$STUDYID, links$USUBJID, links$IDVARVAL, sep = "\r")42)]4344aeseqs <- character(nrow(cm))45aeterms <- character(nrow(cm))46aetermn <- integer(nrow(cm))47for (i in seq_len(nrow(cm))) {48  related <- relae[49    !is.na(relid[i]) & relae$STUDYID == cm$STUDYID[i] &50      relae$USUBJID == cm$USUBJID[i] & relae$RELID == relid[i],51  ]52  if (nrow(related) == 0) {53    aeseqs[i] <- NA_character_54    aeterms[i] <- NA_character_55    aetermn[i] <- NA_integer_56  } else {57    names <- sort(unique(related$AETERM), method = "radix")58    aeseqs[i] <- paste(sort(related$AESEQ), collapse = ", ")59    aeterms[i] <- paste(names, collapse = ", ")60    aetermn[i] <- length(names)61  }62}6364adcm <- data.frame(65  STUDYID = cm$STUDYID,66  USUBJID = cm$USUBJID,67  CMSEQ = as.integer(cm$CMSEQ),68  CMTRT = cm$CMTRT,69  AESEQS = aeseqs,70  AETERMS = aeterms,71  AETERMN = aetermn,72  stringsAsFactors = FALSE73)74adcm <- adcm[order(adcm$STUDYID, adcm$USUBJID, adcm$CMSEQ, method = "radix"), ]7576dir.create("/app/output", showWarnings = FALSE, recursive = TRUE)77write.csv(relae, "/app/output/relae.csv", row.names = FALSE, na = "")78write.csv(adcm, "/app/output/adcm.csv", row.names = FALSE, na = "")

solutions/adam-adcm-related-events/result.py

Edit97 lines

1# Reference solution for the yamaa benchmark adam-adcm-related-events (Python track).2#3# Written from the benchmark's full prompt and its inputs alone, as an agent4# would write it. Harbor's oracle agent runs it to check that the prompt can5# be solved and that the grader scores a correct answer 1.67import csv8from pathlib import Path910INPUT_DIR = Path("/app/input")11OUTPUT_DIR = Path("/app/output")12RELAE_COLUMNS = ["STUDYID", "USUBJID", "RELID", "AESEQ", "AETERM"]13ADCM_COLUMNS = [14    "STUDYID",15    "USUBJID",16    "CMSEQ",17    "CMTRT",18    "AESEQS",19    "AETERMS",20    "AETERMN",21]222324def read(name: str) -> list[dict[str, str]]:25    with open(INPUT_DIR / name, newline="", encoding="utf-8") as handle:26        return list(csv.DictReader(handle))272829def write(name: str, columns: list[str], rows: list[dict]) -> None:30    OUTPUT_DIR.mkdir(parents=True, exist_ok=True)31    with open(OUTPUT_DIR / name, "w", newline="", encoding="utf-8") as handle:32        writer = csv.writer(handle, lineterminator="\n")33        writer.writerow(columns)34        for row in rows:35            writer.writerow(["" if row[c] is None else row[c] for c in columns])363738def main() -> None:39    ae = read("ae.csv")40    cm = read("cm.csv")41    relrec = read("relrec.csv")4243    # Each adverse event a relationship names, with the event's reported term.44    terms = {(r["STUDYID"], r["USUBJID"], int(r["AESEQ"])): r["AETERM"] for r in ae}45    relae = []46    for r in relrec:47        if r["RDOMAIN"] == "AE" and r["IDVAR"] == "AESEQ":48            seq = int(r["IDVARVAL"])49            relae.append(50                {51                    "STUDYID": r["STUDYID"],52                    "USUBJID": r["USUBJID"],53                    "RELID": r["RELID"],54                    "AESEQ": seq,55                    "AETERM": terms[(r["STUDYID"], r["USUBJID"], seq)],56                }57            )58    relae.sort(key=lambda r: (r["STUDYID"], r["USUBJID"], r["RELID"], r["AESEQ"]))5960    # The relationship each medication belongs to.61    relationship = {62        (r["STUDYID"], r["USUBJID"], r["IDVARVAL"]): r["RELID"]63        for r in relrec64        if r["RDOMAIN"] == "CM" and r["IDVAR"] == "CMSEQ"65    }6667    adcm = []68    for r in cm:69        relid = relationship.get((r["STUDYID"], r["USUBJID"], r["CMSEQ"]))70        related = [71            event72            for event in relae73            if relid is not None74            and (event["STUDYID"], event["USUBJID"], event["RELID"])75            == (r["STUDYID"], r["USUBJID"], relid)76        ]77        sequences = sorted(event["AESEQ"] for event in related)78        names = sorted({event["AETERM"] for event in related})79        adcm.append(80            {81                "STUDYID": r["STUDYID"],82                "USUBJID": r["USUBJID"],83                "CMSEQ": int(r["CMSEQ"]),84                "CMTRT": r["CMTRT"],85                "AESEQS": ", ".join(str(s) for s in sequences) or None,86                "AETERMS": ", ".join(names) or None,87                "AETERMN": len(names) or None,88            }89        )90    adcm.sort(key=lambda r: (r["STUDYID"], r["USUBJID"], r["CMSEQ"]))9192    write("relae.csv", RELAE_COLUMNS, relae)93    write("adcm.csv", ADCM_COLUMNS, adcm)949596if __name__ == "__main__":97    main()

solutions/adam-adcm-related-events/result.sas

Edit119 lines

1/* opensas reference solution for the yamaa benchmark adam-adcm-related-events.2   Reads the benchmark inputs and derives the requested outputs.3   Execute with the existing opensas runtime: opensas /app/output/result.sas. */45data ae;6  length STUDYID USUBJID $40 AETERM $200;7  infile "/app/input/ae.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;8  input STUDYID : $char40. USUBJID : $char40. AESEQ AETERM : $char200.;9run;1011data cm;12  length STUDYID USUBJID $40 CMTRT $200;13  infile "/app/input/cm.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;14  input STUDYID : $char40. USUBJID : $char40. CMSEQ CMTRT : $char200.;15run;1617data relrec;18  length STUDYID RDOMAIN USUBJID IDVAR IDVARVAL RELTYPE RELID $40;19  infile "/app/input/relrec.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;20  input STUDYID : $char40. RDOMAIN : $char40. USUBJID : $char40.21        IDVAR : $char40. IDVARVAL : $char40. RELTYPE : $char40.22        RELID : $char40.;23run;2425/* The medications and the adverse events each relationship names, with26   their numeric sequence numbers. Function calls in join predicates were27   rejected by the release, so the keys are calculated before joining. */28data relcm;29  set relrec;30  if RDOMAIN = 'CM' and IDVAR = 'CMSEQ';31  CMSEQ = input(IDVARVAL, best32.);32  keep STUDYID USUBJID RELID CMSEQ;33run;3435data relaeseq;36  set relrec;37  if RDOMAIN = 'AE' and IDVAR = 'AESEQ';38  AESEQ = input(IDVARVAL, best32.);39  keep STUDYID USUBJID RELID AESEQ;40run;4142proc sql;43  /* Each adverse event a relationship names, with its reported term. */44  create table relae as45    select r.STUDYID, r.USUBJID, r.RELID, r.AESEQ, a.AETERM46    from relaeseq as r left join ae as a47      on a.STUDYID = r.STUDYID and a.USUBJID = r.USUBJID48         and a.AESEQ = r.AESEQ49    order by r.STUDYID, r.USUBJID, r.RELID, r.AESEQ;50  /* The relationship each medication belongs to. */51  create table cmrel as52    select c.STUDYID, c.USUBJID, c.CMSEQ, c.CMTRT, r.RELID53    from cm as c left join relcm as r54      on r.STUDYID = c.STUDYID and r.USUBJID = c.USUBJID55         and r.CMSEQ = c.CMSEQ;56  create table pairs as57    select m.STUDYID, m.USUBJID, m.CMSEQ, e.AESEQ, e.AETERM58    from cmrel as m inner join relae as e59      on e.STUDYID = m.STUDYID and e.USUBJID = m.USUBJID60         and e.RELID = m.RELID;61quit;6263/* The related sequence numbers in numeric order. */64proc sort data=pairs out=byseq;65  by STUDYID USUBJID CMSEQ AESEQ;66run;6768data seqs;69  length AESEQS $1000;70  retain AESEQS;71  set byseq;72  by STUDYID USUBJID CMSEQ;73  if first.CMSEQ then AESEQS = '';74  AESEQS = catx(', ', AESEQS, strip(put(AESEQ, best32.)));75  if last.CMSEQ then output;76  keep STUDYID USUBJID CMSEQ AESEQS;77run;7879/* The different related terms in alphabetical order, and their number. */80data termpairs;81  set pairs;82  keep STUDYID USUBJID CMSEQ AETERM;83run;8485proc sort data=termpairs out=byterm nodupkey;86  by STUDYID USUBJID CMSEQ AETERM;87run;8889data terms;90  length AETERMS $1000;91  retain AETERMS AETERMN;92  set byterm;93  by STUDYID USUBJID CMSEQ;94  if first.CMSEQ then do;95    AETERMS = '';96    AETERMN = 0;97  end;98  AETERMS = catx(', ', AETERMS, AETERM);99  AETERMN = AETERMN + 1;100  if last.CMSEQ then output;101  keep STUDYID USUBJID CMSEQ AETERMS AETERMN;102run;103104proc sql;105  create table adcm as106    select m.STUDYID, m.USUBJID, m.CMSEQ, m.CMTRT,107           s.AESEQS, t.AETERMS, t.AETERMN108    from cmrel as m109      left join seqs as s110        on s.STUDYID = m.STUDYID and s.USUBJID = m.USUBJID111           and s.CMSEQ = m.CMSEQ112      left join terms as t113        on t.STUDYID = m.STUDYID and t.USUBJID = m.USUBJID114           and t.CMSEQ = m.CMSEQ115    order by m.STUDYID, m.USUBJID, m.CMSEQ;116quit;117118proc export data=relae outfile='/app/output/relae.csv' dbms=csv replace; run;119proc export data=adcm outfile='/app/output/adcm.csv' dbms=csv replace; run;

input/ae.csv

input/cm.csv

input/relrec.csv

expected/adcm.csv

expected/relae.csv

Your review

Mapping spec

Agent prompt

prompts/adam-adcm-related-events/full.md

prompts/adam-adcm-related-events/conventions.md

prompts/adam-adcm-related-events/brief.md

yamaa code

R

Python

Solution without yamaa

solutions/adam-adcm-related-events/result.R

solutions/adam-adcm-related-events/result.py

solutions/adam-adcm-related-events/result.sas