Flag Any Reported Dose Adjustment

1library(yamaa)23adsl <- yamaa_domain("spec.yaml")$output4adsl

1import yamaa23adsl = yamaa.yamaa_domain("spec.yaml").output4adsl

1# Reference solution for the yamaa benchmark adam-adsl-dose-adjustment (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)9library(stringr)1011base <- read_csv(12  "/app/input/adsl.csv",13  col_types = cols(.default = col_character())14)15ex <- read_csv(16  "/app/input/ex.csv",17  col_types = cols(.default = col_character())18)19ec <- read_csv(20  "/app/input/ec.csv",21  col_types = cols(.default = col_character())22)23fa <- read_csv(24  "/app/input/fa.csv",25  col_types = cols(.default = col_character())26)2728# A record reports an adjustment with a filled value; findings-about rows29# qualify only for dose adjustment occurrences with a Y result.30ex_adj <- ex |>31  filter(!is.na(EXADJ), str_trim(EXADJ) != "") |>32  distinct(STUDYID, USUBJID) |>33  mutate(.ex_adj = TRUE)34ec_adj <- ec |>35  filter(!is.na(ECADJ), str_trim(ECADJ) != "") |>36  distinct(STUDYID, USUBJID) |>37  mutate(.ec_adj = TRUE)38fa_adj <- fa |>39  filter(FATESTCD %in% "OCCUR", FAOBJ %in% "DOSE ADJUSTMENT", FASTRESC %in% "Y") |>40  distinct(STUDYID, USUBJID) |>41  mutate(.fa_adj = TRUE)4243ex_any <- ex |> distinct(STUDYID, USUBJID) |> mutate(.ex_any = TRUE)44ec_any <- ec |> distinct(STUDYID, USUBJID) |> mutate(.ec_any = TRUE)45fa_any <- fa |> distinct(STUDYID, USUBJID) |> mutate(.fa_any = TRUE)4647adsl <- base |>48  left_join(ex_adj, by = c("STUDYID", "USUBJID")) |>49  left_join(ec_adj, by = c("STUDYID", "USUBJID")) |>50  left_join(fa_adj, by = c("STUDYID", "USUBJID")) |>51  left_join(ex_any, by = c("STUDYID", "USUBJID")) |>52  left_join(ec_any, by = c("STUDYID", "USUBJID")) |>53  left_join(fa_any, by = c("STUDYID", "USUBJID")) |>54  mutate(55    DOSADJFL = case_when(56      .ex_adj %in% TRUE | .ec_adj %in% TRUE | .fa_adj %in% TRUE ~ "Y",57      .ex_any %in% TRUE | .ec_any %in% TRUE | .fa_any %in% TRUE ~ "N"58    )59  ) |>60  select(STUDYID, USUBJID, DOSADJFL)6162dir.create("/app/output", showWarnings = FALSE)63write_csv(adsl, "/app/output/adsl.csv", na = "")

1# Reference solution for the yamaa benchmark adam-adsl-dose-adjustment (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 1.67from pathlib import Path89import polars as pl1011base = pl.read_csv("/app/input/adsl.csv", infer_schema=False)12ex = pl.read_csv("/app/input/ex.csv", infer_schema=False)13ec = pl.read_csv("/app/input/ec.csv", infer_schema=False)14fa = pl.read_csv("/app/input/fa.csv", infer_schema=False)1516keys = ["STUDYID", "USUBJID"]1718def adjusted(sub: pl.DataFrame, column: str) -> pl.DataFrame:19    return (20        sub.filter(pl.col(column).fill_null("").str.strip_chars() != "")21        .select(keys)22        .unique()23        .with_columns(pl.lit(True).alias(f"__adj_{column}"))24    )252627def any_records(sub: pl.DataFrame, tag: str) -> pl.DataFrame:28    return (29        sub.select(keys).unique().with_columns(pl.lit(True).alias(f"__any_{tag}"))30    )313233ex_adj = adjusted(ex, "EXADJ")34ec_adj = adjusted(ec, "ECADJ")35fa_adj = (36    fa.filter(37        (pl.col("FATESTCD") == "OCCUR")38        & (pl.col("FAOBJ") == "DOSE ADJUSTMENT")39        & (pl.col("FASTRESC") == "Y")40    )41    .select(keys)42    .unique()43    .with_columns(pl.lit(True).alias("__adj_FA"))44)45ex_any = any_records(ex, "EX")46ec_any = any_records(ec, "EC")47fa_any = any_records(fa, "FA")4849adsl = (50    base.join(ex_adj, on=keys, how="left", maintain_order="left")51    .join(ec_adj, on=keys, how="left", maintain_order="left")52    .join(fa_adj, on=keys, how="left", maintain_order="left")53    .join(ex_any, on=keys, how="left", maintain_order="left")54    .join(ec_any, on=keys, how="left", maintain_order="left")55    .join(fa_any, on=keys, how="left", maintain_order="left")56    .with_columns(57        DOSADJFL=pl.when(58            (pl.col("__adj_EXADJ") == True)59            | (pl.col("__adj_ECADJ") == True)60            | (pl.col("__adj_FA") == True)61        )62        .then(pl.lit("Y"))63        .when(64            (pl.col("__any_EX") == True)65            | (pl.col("__any_EC") == True)66            | (pl.col("__any_FA") == True)67        )68        .then(pl.lit("N"))69        .otherwise(None)70    )71    .select("STUDYID", "USUBJID", "DOSADJFL")72)7374Path("/app/output").mkdir(exist_ok=True)75adsl.write_csv("/app/output/adsl.csv")

1/* opensas reference solution for the yamaa benchmark adam-adsl-dose-adjustment.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 $1024;7  infile "/app/input/adsl.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;8  input STUDYID : $char1024. USUBJID : $char1024.;9run;1011data ec;12  length STUDYID USUBJID ECADJ $1024;13  infile "/app/input/ec.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;14  input STUDYID : $char1024. USUBJID : $char1024. ECADJ : $char1024.;15run;1617data ex;18  length STUDYID USUBJID EXADJ $1024;19  infile "/app/input/ex.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;20  input STUDYID : $char1024. USUBJID : $char1024. EXADJ : $char1024.;21run;2223data fa;24  length STUDYID USUBJID FATESTCD FAOBJ FASTRESC $1024;25  infile "/app/input/fa.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;26  input STUDYID : $char1024. USUBJID : $char1024. FATESTCD : $char1024. FAOBJ : $char1024. FASTRESC : $char1024.;27run;2829proc sql;30  create table evidence as31  select STUDYID,USUBJID,case when not missing(EXADJ) then 1 else 0 end as adjusted from ex32  union all select STUDYID,USUBJID,case when not missing(ECADJ) then 1 else 0 end from ec33  union all select STUDYID,USUBJID,case when FATESTCD='OCCUR' and FAOBJ='DOSE ADJUSTMENT' and FASTRESC='Y' then 1 else 0 end from fa;34  create table flags as select STUDYID,USUBJID,max(adjusted) as adjusted,count(*) as records from evidence group by STUDYID,USUBJID;35  create table result as select a.*, case when b.adjusted=1 then 'Y' when b.records>0 then 'N' else '' end as DOSADJFL from adsl as a left join flags as b on a.STUDYID=b.STUDYID and a.USUBJID=b.USUBJID;36quit;3738proc sql;39  create table final as select STUDYID, USUBJID, DOSADJFL from result;40quit;41proc export data=final outfile="/app/output/adsl.csv" dbms=csv replace; run;