Clinical Site Data at Site Level

1library(yamaa)23yamaa_spec("spec.yaml")$run()$output

1import yamaa23yamaa.spec("spec.yaml").run().output

1# Reference solution for the yamaa benchmark adam-clinsite-site-level (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 1.67library(dplyr, warn.conflicts = FALSE)8library(readr)910subj <- read_csv(11  "/app/input/adsl.csv",12  col_types = cols(.default = col_character())13)1415clinsite <- subj |>16  # One record per site; the site key stays text so leading zeros survive.17  group_by(STUDYID, SITENUM) |>18  summarise(19    # The alphabetically first arm among the site's treated subjects.20    # A blank (missing) SAFFL counts as not "Y" so it can neither enter21    # the treated arm list nor turn the treated count missing.22    ARM = {23      treated <- !is.na(SAFFL) & SAFFL == "Y"24      treated_arms <- ARM[treated]25      if (length(treated_arms)) min(treated_arms) else NA_character_26    },27    # Treated subjects, then all enrolled subjects, at the site.28    SAFPOP = sum(!is.na(SAFFL) & SAFFL == "Y"),29    ENRLPOP = n(),30    .groups = "drop"31  ) |>32  rename(SITEID = SITENUM) |>33  select(STUDYID, SITEID, ARM, SAFPOP, ENRLPOP) |>34  arrange(SITEID)3536dir.create("/app/output", showWarnings = FALSE)37write_csv(clinsite, "/app/output/clinsite.csv", na = "")

1# Reference solution for the yamaa benchmark adam-clinsite-site-level (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 1.67"""Build CLINSITE (one record per clinical site) from ADSL.89Reads /app/input/adsl.csv and writes /app/output/clinsite.csv with10columns STUDYID, SITEID, ARM, SAFPOP, ENRLPOP.1112Rules:13- A subject counts as treated when SAFFL is "Y".14- A site appears exactly when at least one subject row names it.15- SITEID is the site key exactly as collected (SITENUM); leading zeros16  are kept, so "007" and "7" are different sites.17- ARM is the alphabetically first arm among the site's treated18  subjects, blank when the site has no treated subjects.19- SAFPOP is the number of treated subjects at the site (0 when none).20- ENRLPOP is the number of enrolled subjects at the site.21"""2223import csv24import os25from collections import OrderedDict2627INPUT_DIR = "/app/input"28OUTPUT_DIR = "/app/output"293031def main():32    with open(os.path.join(INPUT_DIR, "adsl.csv"), newline="") as f:33        rows = list(csv.DictReader(f))3435    sites = OrderedDict()36    for row in rows:37        site = row["SITENUM"]38        entry = sites.setdefault(39            site,40            {"studyid": row["STUDYID"], "treated_arms": [], "safpop": 0, "enrlpop": 0},41        )42        entry["enrlpop"] += 143        if row["SAFFL"] == "Y":44            entry["safpop"] += 145            entry["treated_arms"].append(row["ARM"])4647    out_rows = []48    for site, entry in sites.items():49        arm = min(entry["treated_arms"]) if entry["treated_arms"] else ""50        out_rows.append(51            {52                "STUDYID": entry["studyid"],53                "SITEID": site,54                "ARM": arm,55                "SAFPOP": entry["safpop"],56                "ENRLPOP": entry["enrlpop"],57            }58        )5960    os.makedirs(OUTPUT_DIR, exist_ok=True)61    with open(os.path.join(OUTPUT_DIR, "clinsite.csv"), "w", newline="") as f:62        writer = csv.DictWriter(63            f, fieldnames=["STUDYID", "SITEID", "ARM", "SAFPOP", "ENRLPOP"]64        )65        writer.writeheader()66        writer.writerows(out_rows)676869if __name__ == "__main__":70    main()

1/* opensas reference solution for the yamaa benchmark adam-clinsite-site-level.2   Reads the benchmark inputs and derives the requested output.3   Execute with the existing opensas runtime: opensas /app/output/result.sas. */45data adsl;6  length STUDYID USUBJID SITENUM ARM SAFFL $1024;7  infile "/app/input/adsl.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;8  input STUDYID : $char1024. USUBJID : $char1024. SITENUM : $char1024. ARM : $char1024. SAFFL : $char1024.;9run;1011proc sql;12create table counts as select STUDYID,SITENUM,count(*) as ENRLPOP,sum(case when SAFFL='Y' then 1 else 0 end) as SAFPOP from adsl group by STUDYID,SITENUM;13create table arms as select STUDYID,SITENUM,min(ARM) as ARM from adsl where SAFFL='Y' group by STUDYID,SITENUM;14create table result as select a.STUDYID,a.SITENUM as SITEID,b.ARM,a.SAFPOP,a.ENRLPOP from counts a left join arms b on a.STUDYID=b.STUDYID and a.SITENUM=b.SITENUM;15quit;16proc export data=result(keep=STUDYID SITEID ARM SAFPOP ENRLPOP) outfile="/app/output/clinsite.csv" dbms=csv replace; run;