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Summary

Lifecycle: draftEditUnder review
What this benchmark means
README.md

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

Goal: build one record per collected tumor assessment, carrying the collected test, result, unit, method, evaluator, and visit through and adding the standardized numeric result, text result, and standard unit: TRTESTCD, TRTEST, TRORRES, TRORRESU, TRSTRESN, TRSTRESC, TRSTRESU, and TRSTAT.

Input: collected lesion assessments with one row per lesion per visit, carrying the collected result and unit plus study, subject, sequence (TRSEQ), link, method, evaluator, visit, and date identifiers.

Variables:

  • TRLNKID is the link identifier tying the assessment to its lesion in the tumor identification (TU) domain; target, non-target, and new lesions each keep their own identifier.
  • TRTESTCD is the test code as collected: DIAMETER for a measured lesion or TUMSTATE for a lesion state.
  • TRTEST is the test name as collected: Diameter or Tumor State.
  • TRORRES is the result exactly as collected, never overwritten: a diameter, TOO SMALL TO MEASURE, a state such as PRESENT, or empty when the lesion was not assessed.
  • TRORRESU is the unit exactly as collected: mm or cm for a diameter, empty otherwise.
  • TRSTRESC is the standardized character result: a diameter in mm written as text, 5 for a lesion too small to measure, a lesion state kept as collected, and empty when the lesion was not assessed.
  • TRSTRESN is the standardized numeric result in mm: a diameter passes through, a value collected in cm is multiplied by 10, and a lesion too small to measure takes the study convention of 5 mm; it stays empty for lesion states and for lesions not assessed.
  • TRSTRESU is mm whenever a standardized numeric result exists, empty otherwise.
  • TRSTAT is NOT DONE for a lesion not assessed at a visit, empty otherwise.
  • TRMETHOD is the measurement method as collected.
  • TREVAL names the evaluator as collected.
  • VISITNUM is the visit number as collected.
  • TRDTC is the assessment date as collected, empty when the lesion was not assessed.

Note: a lymph-node target lesion contributes its short axis as its diameter, following the study's response criteria; that axis is already the value the sum of diameters needs, so it is carried like any other diameter. A lesion too small to measure is not a zero: it takes the study's conventional 5 mm, and a lesion not assessed stays out of every standardized column rather than counting as zero.

Inputs

Under review
1 source file

input/tr_raw.csv

Edit
10 rows
input/tr_raw.csv
STUDYIDUSUBJIDTRSEQTRLNKIDTRTESTCDTRTESTTRORRESTRORRESUTRSTATTRMETHODTREVALVISITNUMTRDTC
YAMAA-011T01DIAMETERDiameter32mm—CT SCANINVESTIGATOR12026-01-05
YAMAA-012T01DIAMETERDiameter2.8cm—CT SCANINVESTIGATOR22026-03-02
YAMAA-013T01DIAMETERDiameter25mm—CT SCANINVESTIGATOR32026-04-27
YAMAA-014T02DIAMETERDiameter18mm—CT SCANINVESTIGATOR12026-01-05
YAMAA-015T02DIAMETERDiameter——NOT DONECT SCANINVESTIGATOR2—
YAMAA-016T02DIAMETERDiameterTOO SMALL TO MEASUREmm—CT SCANINVESTIGATOR32026-04-27
YAMAA-017NT01TUMSTATETumor StatePRESENT——CT SCANINVESTIGATOR12026-01-05
YAMAA-018NT01TUMSTATETumor StatePRESENT——CT SCANINVESTIGATOR22026-03-02
YAMAA-019NT01TUMSTATETumor StateABSENT——CT SCANINVESTIGATOR32026-04-27
YAMAA-0110NEW01TUMSTATETumor StatePRESENT——CT SCANINVESTIGATOR32026-04-27

Expected output

Under review
10 expected rows

expected/tr.csv

Edit
10 rows
expected/tr.csv
DOMAINSTUDYIDUSUBJIDTRSEQTRLNKIDTRTESTCDTRTESTTRORRESTRORRESUTRSTRESCTRSTRESNTRSTRESUTRSTATTRMETHODTREVALVISITNUMTRDTC
TRYAMAA-011T01DIAMETERDiameter32mm3232mm—CT SCANINVESTIGATOR12026-01-05
TRYAMAA-012T01DIAMETERDiameter2.8cm2828mm—CT SCANINVESTIGATOR22026-03-02
TRYAMAA-013T01DIAMETERDiameter25mm2525mm—CT SCANINVESTIGATOR32026-04-27
TRYAMAA-014T02DIAMETERDiameter18mm1818mm—CT SCANINVESTIGATOR12026-01-05
TRYAMAA-015T02DIAMETERDiameter—————NOT DONECT SCANINVESTIGATOR2—
TRYAMAA-016T02DIAMETERDiameterTOO SMALL TO MEASUREmm55mm—CT SCANINVESTIGATOR32026-04-27
TRYAMAA-017NT01TUMSTATETumor StatePRESENT—PRESENT———CT SCANINVESTIGATOR12026-01-05
TRYAMAA-018NT01TUMSTATETumor StatePRESENT—PRESENT———CT SCANINVESTIGATOR22026-03-02
TRYAMAA-019NT01TUMSTATETumor StateABSENT—ABSENT———CT SCANINVESTIGATOR32026-04-27
TRYAMAA-0110NEW01TUMSTATETumor StatePRESENT—PRESENT———CT SCANINVESTIGATOR32026-04-27
Shaded columns are derived— = missing value

Human review and assessment

Your review

3 questions and your comments · View benchmark discussions

Mapping spec

Generated from the benchmark YAML; do not edit by hand

Variable NameVariable LabelTypeLengthControlled Terms or FormatOriginCoreConversion DefinitionVariable TypeVariable OrderComments for Define
DOMAINDomain AbbreviationCharAssignedSet constant value "TR".SDTM1
STUDYIDStudy IdentifierCharCollectedCopy value from TR_RAW.STUDYID.SDTM2
USUBJIDUnique Subject IdentifierCharCollectedCopy value from TR_RAW.USUBJID.SDTM3
TRSEQSequence NumberNumCollectedCopy value from TR_RAW.TRSEQ.SDTM4
TRLNKIDLink IDCharCollectedCopy value from TR_RAW.TRLNKID.SDTM5
TRTESTCDTumor Result Test Short NameCharDIAMETER, TUMSTATECollectedCopy value from TR_RAW.TRTESTCD.SDTM6
TRTESTTumor Result Test NameCharCollectedCopy value from TR_RAW.TRTEST.SDTM7
TRORRESResult or Finding in Original UnitsCharCollectedCopy value from TR_RAW.TRORRES.SDTM8
TRORRESUOriginal UnitsCharmm, cmCollectedCopy value from TR_RAW.TRORRESU.SDTM9
TRSTRESNNumeric Result/Finding in Standard UnitsNumDerivedIf TR_RAW.TRORRES = 'TOO SMALL TO MEASURE' then "5"; If TR_RAW.TRTESTCD = 'DIAMETER' AND TR_RAW.TRORRESU = 'cm' then compute TRORRES_N * 10; If TR_RAW.TRTESTCD = 'DIAMETER' then "TRORRES_N"; otherwise blank.SDTM10
TRSTRESCCharacter Result/Finding in Std FormatCharDerivedIf TR_RAW.TRTESTCD = 'DIAMETER' then "TRSTRESN"; otherwise "TR_RAW.TRORRES".SDTM11
TRSTRESUStandard UnitsCharmmDerivedIf TRSTRESN IS NOT NULL then "mm"; otherwise blank.SDTM12
TRSTATCompletion StatusCharNOT DONECollectedCopy value from TR_RAW.TRSTAT.SDTM13
TRMETHODMethod of Test or ExaminationCharCollectedCopy value from TR_RAW.TRMETHOD.SDTM14
TREVALEvaluatorCharCollectedCopy value from TR_RAW.TREVAL.SDTM15
VISITNUMVisit NumberNumCollectedCopy value from TR_RAW.VISITNUM.SDTM16
TRDTCDate/Time of Tumor MeasurementCharISO 8601CollectedCopy value from TR_RAW.TRDTC.SDTM17
VariablePermitted values
TRTESTCDDIAMETER, TUMSTATE
TRORRESUmm, cm
TRSTRESUmm
TRSTATNOT DONE
VersionDateAuthorDescriptionReviewerSign-off
1.72026-10-20yamaa docs buildRead 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
1.62026-10-17yamaa docs buildDescribe collected date parts written as ISO 8601 date text and times of day counted in seconds since midnight
1.52026-10-17yamaa docs buildName 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
1.42026-10-15yamaa docs buildState datetime precision codes through the hour and minute, and complete only the time parts a collected datetime lacks
1.32026-09-29yamaa docs buildShow study codelist names, external dictionaries, and ISO 8601 formats in variable rows; list the document's codelist values and metadata
1.22026-09-29yamaa docs buildClassify ADaM copies from a declared input as Predecessor and recodes as Derived, and SDTM recodes of locally derived columns as Derived
1.12026-09-29yamaa docs buildResolve lookups into the donor record they select, and give every derivation shape a plain-language rule instead of its raw YAML
1.0yamaa docs buildInitial generation from spec.yaml

Agent prompt

The request an agent receives with the input files; each tier states no more than the one above

prompts/sdtm-tr-tumor-measurements/full.md

Edit
30 lines

Following CDISC SDTM standards, use the provided TR_RAW dataset to create a TR dataset with one record per collected tumor assessment.

The output dataset should contain the following columns in this order: DOMAIN, STUDYID, USUBJID, TRSEQ, TRLNKID, TRTESTCD, TRTEST, TRORRES, TRORRESU, TRSTRESC, TRSTRESN, TRSTRESU, TRSTAT, TRMETHOD, TREVAL, VISITNUM, TRDTC

DOMAIN is "TR". STUDYID and USUBJID are as given in TR_RAW, and TRSEQ is the sequence number as collected. TRLNKID is the link identifier tying the assessment to its lesion in the tumor identification (TU) domain; target, non-target, and new lesions each keep their own identifier. TRTESTCD is the test code as collected: "DIAMETER" for a measured lesion or "TUMSTATE" for a lesion state. TRTEST is the test name as collected: "Diameter" or "Tumor State". TRORRES is the result exactly as collected: a diameter, "TOO SMALL TO MEASURE", a state such as "PRESENT", or no value when the lesion was not assessed. TRORRESU is the unit exactly as collected: "mm" or "cm" for a diameter, and no value otherwise. TRSTRESN is the standardized numeric result in mm: a diameter collected in mm keeps its collected value, a diameter collected in cm is multiplied by 10, and a lesion too small to measure takes 5. TRSTRESN has no value for a lesion state or for a lesion that was not assessed. TRSTRESC is the standardized character result: for a diameter, the standardized numeric result in mm written as text, so a lesion too small to measure gives "5"; a lesion state is kept as collected; and it has no value when the lesion was not assessed. TRSTRESU is "mm" whenever TRSTRESN has a value, and has no value otherwise. TRSTAT is "NOT DONE" for a lesion not assessed at a visit, and has no value otherwise.

Read the source datasets from /app/input and save the completed dataset as /app/output/tr.csv.

prompts/sdtm-tr-tumor-measurements/conventions.md

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12 lines

Following CDISC SDTM standards, use the provided TR_RAW dataset to create a TR dataset with one record per collected tumor assessment.

The output dataset should contain the following columns in this order: DOMAIN, STUDYID, USUBJID, TRSEQ, TRLNKID, TRTESTCD, TRTEST, TRORRES, TRORRESU, TRSTRESC, TRSTRESN, TRSTRESU, TRSTAT, TRMETHOD, TREVAL, VISITNUM, TRDTC

DOMAIN is "TR". TRTESTCD is "DIAMETER" or "TUMSTATE", and TRTEST is "Diameter" or "Tumor State". TRSTAT is "NOT DONE" or has no value.

Read the source datasets from /app/input and save the completed dataset as /app/output/tr.csv.

prompts/sdtm-tr-tumor-measurements/brief.md

Edit
9 lines

Following CDISC SDTM standards, use the provided TR_RAW dataset to create a TR dataset with one record per collected tumor assessment.

The output dataset should contain the following columns in this order: DOMAIN, STUDYID, USUBJID, TRSEQ, TRLNKID, TRTESTCD, TRTEST, TRORRES, TRORRESU, TRSTRESC, TRSTRESN, TRSTRESU, TRSTAT, TRMETHOD, TREVAL, VISITNUM, TRDTC

Read the source datasets from /app/input and save the completed dataset as /app/output/tr.csv.

yamaa code

Public calls generated from benchmark.yaml; results must match the expected output

R

Edit
3 lines
library(yamaa)yamaa_spec("spec.yaml")$run()$output

Python

Edit
3 lines
import yamaayamaa.spec("spec.yaml").run().output

Solution without yamaa

Written from the full prompt and the inputs alone; CI checks it reproduces the expected output

solutions/sdtm-tr-tumor-measurements/result.R

Edit
61 lines
# Reference solution for the yamaa benchmark sdtm-tr-tumor-measurements (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)fmt_num <- function(x) {  if (is.na(x)) {    return(NA_character_)  }  if (x == floor(x)) {    formatC(x, format = "f", digits = 0)  } else {    formatted <- format(x, scientific = FALSE, trim = TRUE, digits = 15)    sub("\\.0+$", "", formatted)  }}raw <- read_csv(  "/app/input/tr_raw.csv",  col_types = cols(    TRSEQ = col_integer(),    VISITNUM = col_integer(),    .default = col_character()  ))tr <- raw |>  mutate(    orres_num = suppressWarnings(as.numeric(TRORRES)),    mm_value = if_else(TRORRESU == "cm", orres_num * 10, orres_num),    TRSTRESN = case_when(      TRTESTCD == "DIAMETER" & TRORRES == "TOO SMALL TO MEASURE" ~ 5,      TRTESTCD == "DIAMETER" & !is.na(TRORRES) & TRORRES != "" &        TRORRES != "TOO SMALL TO MEASURE" ~ mm_value,      .default = NA_real_    ),    TRSTRESC = case_when(      TRTESTCD == "DIAMETER" & TRORRES == "TOO SMALL TO MEASURE" ~ "5",      TRTESTCD == "DIAMETER" & !is.na(TRORRES) & TRORRES != "" &        TRORRES != "TOO SMALL TO MEASURE" ~ vapply(        TRSTRESN, fmt_num, character(1)      ),      TRTESTCD != "DIAMETER" & !is.na(TRORRES) & TRORRES != "" ~ TRORRES,      .default = NA_character_    ),    DOMAIN = "TR",    TRSTRESU = if_else(!is.na(TRSTRESN), "mm", NA_character_)  ) |>  arrange(USUBJID, TRSEQ) |>  select(    DOMAIN, STUDYID, USUBJID, TRSEQ, TRLNKID, TRTESTCD, TRTEST, TRORRES,    TRORRESU, TRSTRESC, TRSTRESN, TRSTRESU, TRSTAT, TRMETHOD, TREVAL,    VISITNUM, TRDTC  )dir.create("/app/output", showWarnings = FALSE)write_csv(tr, "/app/output/tr.csv", na = "")

solutions/sdtm-tr-tumor-measurements/result.py

Edit
95 lines
# Reference solution for the yamaa benchmark sdtm-tr-tumor-measurements (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."""Build the SDTM TR dataset from TR_RAW.One record per collected tumor assessment. Diameter results arestandardized to mm: a value collected in mm keeps its value, a valuecollected in cm is multiplied by 10, and a lesion too small to measuretakes 5. Lesion states are kept as collected. A lesion that was notassessed carries TRSTAT "NOT DONE" and no standardized result."""import csvimport osINPUT_DIR = "/app/input"OUTPUT_DIR = "/app/output"TOO_SMALL = "TOO SMALL TO MEASURE"TOO_SMALL_MM = 5.0OUT_COLUMNS = [    "DOMAIN", "STUDYID", "USUBJID", "TRSEQ", "TRLNKID", "TRTESTCD",    "TRTEST", "TRORRES", "TRORRESU", "TRSTRESC", "TRSTRESN", "TRSTRESU",    "TRSTAT", "TRMETHOD", "TREVAL", "VISITNUM", "TRDTC",]def fmt_number(value):    """Write a float without a trailing .0 or float artifacts."""    if value == int(value):        return str(int(value))    return repr(value)def main():    with open(os.path.join(INPUT_DIR, "tr_raw.csv"), newline="") as fh:        rows = list(csv.DictReader(fh))    out_rows = []    for row in rows:        testcd = row["TRTESTCD"]        orres = row["TRORRES"]        orresu = row["TRORRESU"]        stat = row["TRSTAT"]        stresn = ""        stresc = ""        if testcd == "DIAMETER":            if orres == TOO_SMALL:                stresn = fmt_number(TOO_SMALL_MM)                stresc = stresn            elif orres != "":                value = float(orres)                if orresu == "cm":                    value = value * 10                stresn = fmt_number(value)                stresc = stresn        elif testcd == "TUMSTATE":            stresc = orres        stresu = "mm" if stresn != "" else ""        out_rows.append({            "DOMAIN": "TR",            "STUDYID": row["STUDYID"],            "USUBJID": row["USUBJID"],            "TRSEQ": row["TRSEQ"],            "TRLNKID": row["TRLNKID"],            "TRTESTCD": testcd,            "TRTEST": row["TRTEST"],            "TRORRES": orres,            "TRORRESU": orresu,            "TRSTRESC": stresc,            "TRSTRESN": stresn,            "TRSTRESU": stresu,            "TRSTAT": stat,            "TRMETHOD": row["TRMETHOD"],            "TREVAL": row["TREVAL"],            "VISITNUM": row["VISITNUM"],            "TRDTC": row["TRDTC"],        })    os.makedirs(OUTPUT_DIR, exist_ok=True)    with open(os.path.join(OUTPUT_DIR, "tr.csv"), "w", newline="") as fh:        writer = csv.DictWriter(fh, fieldnames=OUT_COLUMNS)        writer.writeheader()        writer.writerows(out_rows)if __name__ == "__main__":    main()

solutions/sdtm-tr-tumor-measurements/result.sas

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19 lines
/* opensas reference solution for the yamaa benchmark sdtm-tr-tumor-measurements.   Reads the benchmark inputs and derives the requested output.   Execute with the existing opensas runtime: opensas /app/output/result.sas. */data tr_raw;  length STUDYID USUBJID TRLNKID TRTESTCD TRTEST TRORRES TRORRESU TRSTAT TRMETHOD TREVAL TRDTC $1024;  infile "/app/input/tr_raw.csv" dsd dlm="," firstobs=2 truncover lrecl=32767;  input STUDYID : $char1024. USUBJID : $char1024. TRSEQ TRLNKID : $char1024. TRTESTCD : $char1024. TRTEST : $char1024. TRORRES : $char1024. TRORRESU : $char1024. TRSTAT : $char1024. TRMETHOD : $char1024. TREVAL : $char1024. VISITNUM TRDTC : $char1024.;run;data result; set tr_raw; length DOMAIN $2 TRSTRESC TRSTRESU $1024; DOMAIN='TR'; TRSTRESN=.; TRSTRESC=''; TRSTRESU='';if TRSTAT='NOT DONE' or missing(TRORRES) then do; TRSTAT='NOT DONE'; TRORRES=''; TRORRESU=''; TRDTC=''; end;else if TRTESTCD='TUMSTATE' then TRSTRESC=TRORRES;else do; if TRORRES='TOO SMALL TO MEASURE' then TRSTRESN=5; else do; TRSTRESN=input(TRORRES,?? best32.); if TRORRESU='cm' then TRSTRESN=TRSTRESN*10; end;if not missing(TRSTRESN) then do; TRSTRESC=strip(put(TRSTRESN,best32.)); TRSTRESU='mm'; end; end; run;proc sql;  create table final as select DOMAIN, STUDYID, USUBJID, TRSEQ, TRLNKID, TRTESTCD, TRTEST, TRORRES, TRORRESU, TRSTRESC, TRSTRESN, TRSTRESU, TRSTAT, TRMETHOD, TREVAL, VISITNUM, TRDTC from result;quit;proc export data=final outfile="/app/output/tr.csv" dbms=csv replace; run;