Severity Ranking

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

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

1# Reference solution for the yamaa benchmark adam-adae-severity-rank (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(purrr)9library(readr)1011ae <- read_csv(12  "/app/input/ae.csv",13  col_types = cols(AESEQ = col_integer(), .default = col_character())14)1516adae <- ae |>17  mutate(18    ASEV = AESEV,19    ASEVN = case_when(20      ASEV == "MILD" ~ 1L,21      ASEV == "MODERATE" ~ 2L,22      ASEV == "SEVERE" ~ 3L23    )24  ) |>25  group_by(USUBJID) |>26  mutate(27    # Competition rank, worst first; unreported sorts after every reported28    # one and shares one rank. Rank is one plus the count of worse events.29    SEVRANK = map_int(ASEVN, function(v) {30      if (is.na(v)) sum(!is.na(ASEVN)) + 1L else sum(ASEVN > v, na.rm = TRUE) + 1L31    }),32    # Dense rank of the distinct severities, worst first, with unreported33    # as one level after every reported one.34    SEVLVL = map_int(ASEVN, function(v) {35      reported <- unique(ASEVN[!is.na(ASEVN)])36      if (is.na(v)) length(reported) + 1L else sum(reported > v) + 1L37    })38  ) |>39  ungroup() |>40  select(STUDYID, USUBJID, AESEQ, ASEV, ASEVN, SEVRANK, SEVLVL)4142dir.create("/app/output", showWarnings = FALSE)43write_csv(adae, "/app/output/adae.csv", na = "")

1# Reference solution for the yamaa benchmark adam-adae-severity-rank (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 the ADAE severity-rank dataset from the AE dataset.89One record per adverse event. ASEVN is the numeric form of the10reported severity (MILD=1, MODERATE=2, SEVERE=3, blank when no11severity was reported). SEVRANK is the competition rank of the event12within its subject, worst severity first: events sharing a severity13share a rank and the ranks they would otherwise fill are skipped, and14events with no reported severity rank after every reported event and15share one rank. SEVLVL is the dense rank: each distinct severity,16worst first, takes the next number, with an unreported severity17counting as one further distinct severity.18"""1920import csv21import os22from collections import defaultdict2324INPUT_DIR = "/app/input"25OUTPUT_DIR = "/app/output"2627SEVERITY_CODES = {"MILD": 1, "MODERATE": 2, "SEVERE": 3}2829COLUMNS = ["STUDYID", "USUBJID", "AESEQ", "ASEV", "ASEVN", "SEVRANK", "SEVLVL"]303132def main():33    with open(os.path.join(INPUT_DIR, "ae.csv"), newline="") as handle:34        events = list(csv.DictReader(handle))3536    by_subject = defaultdict(list)37    for event in events:38        by_subject[event["USUBJID"]].append(event)3940    rank_of = {}  # id(event) -> (SEVRANK, SEVLVL)41    for subject_events in by_subject.values():42        for event in subject_events:43            event["_asevn"] = SEVERITY_CODES.get(event["AESEV"].strip())4445        reported = [e["_asevn"] for e in subject_events if e["_asevn"] is not None]46        distinct = sorted(set(reported), reverse=True)47        dense = {value: i + 1 for i, value in enumerate(distinct)}48        n_reported = len(reported)4950        for event in subject_events:51            asevn = event["_asevn"]52            if asevn is None:53                # After every event with a reported severity; all54                # unreported events share one rank / one level. With55                # no reported events at all this yields rank 1, level 1.56                sevrank = n_reported + 157                sevlvl = len(distinct) + 158            else:59                sevrank = 1 + sum(1 for value in reported if value > asevn)60                sevlvl = dense[asevn]61            rank_of[id(event)] = (sevrank, sevlvl)6263    os.makedirs(OUTPUT_DIR, exist_ok=True)64    with open(os.path.join(OUTPUT_DIR, "adae.csv"), "w", newline="") as handle:65        writer = csv.DictWriter(handle, fieldnames=COLUMNS)66        writer.writeheader()67        for event in events:68            sevrank, sevlvl = rank_of[id(event)]69            asevn = event["_asevn"]70            writer.writerow(71                {72                    "STUDYID": event["STUDYID"],73                    "USUBJID": event["USUBJID"],74                    "AESEQ": event["AESEQ"],75                    "ASEV": event["AESEV"],76                    "ASEVN": "" if asevn is None else asevn,77                    "SEVRANK": sevrank,78                    "SEVLVL": sevlvl,79                }80            )818283if __name__ == "__main__":84    main()

1/* opensas reference solution for the yamaa benchmark adam-adae-severity-rank.2   Reads the benchmark inputs and derives the requested output.3   Execute with the existing opensas runtime: opensas /app/output/result.sas. */45data ae;6  length STUDYID USUBJID AETERM AESEV $1024;7  infile "/app/input/ae.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;8  input STUDYID : $char1024. USUBJID : $char1024. AESEQ AETERM : $char1024. AESEV : $char1024.;9run;1011data graded;12  length ASEV $20;13  set ae; ASEV=AESEV;14  select(ASEV); when('MILD') ASEVN=1; when('MODERATE') ASEVN=2; when('SEVERE') ASEVN=3; when('LIFE-THREATENING') ASEVN=4; otherwise ASEVN=.; end;15run;16proc sort data=graded; by STUDYID USUBJID descending ASEVN AESEQ; run;17data result;18  set graded; by STUDYID USUBJID descending ASEVN;19  retain count SEVRANK SEVLVL;20  if first.USUBJID then do; count=0; SEVRANK=0; SEVLVL=0; end;21  count+1;22  if first.ASEVN then do; SEVRANK=count; SEVLVL+1; end;23run;2425proc sql;26  create table final as select STUDYID, USUBJID, AESEQ, ASEV, ASEVN, SEVRANK, SEVLVL from result;27quit;28proc export data=final outfile="/app/output/adae.csv" dbms=csv replace; run;