license: cc-by-4.0
language:
- en
pretty_name: PHREEQC-MCQ (verified items and model predictions)
size_categories:
- 1K<n<10K
task_categories:
- question-answering
- multiple-choice
tags:
- chemistry
- geochemistry
- phreeqc
- llm-agents
- tool-use
- scientific-simulation
- benchmark
configs:
- config_name: items
default: true
data_files:
- split: test
path: items.jsonl
- config_name: predictions
data_files:
- split: test
path: predictions.jsonl
PHREEQC-MCQ: verified items and model predictions
Four-option multiple-choice items that require running PHREEQC, a geochemistry simulator from the USGS, together with every per-item model prediction from Same Simulation, Different Evidence: Where Retrieved Tool Output Costs LLM Agents Accuracy.
The items come from PHREEQC-MCQ-200. This release contains the 158 items whose answer keys were reproduced by re-executing PHREEQC 3.8.6; all main-text results of the paper use these items.
The agent harness, the frozen PHREEQC database, and full agent trajectories are on GitHub: grenadeComing/same-simulation-different-evidence.
Load
from datasets import load_dataset
items = load_dataset("grenadeComing/same-simulation-different-evidence", "items", split="test")
predictions = load_dataset("grenadeComing/same-simulation-different-evidence", "predictions", split="test")
Fields
items (158 rows)
| Field | Meaning |
|---|---|
id |
Item id (numbering of the original 200-item pool) |
question |
The prompt given to models, options included |
answer |
Correct option letter |
predictions (8,851 rows: one per run and item)
| Field | Meaning |
|---|---|
run |
Run directory under result/ in the GitHub repository |
model |
Model |
setting |
agent, no_tools, or paired_replay |
condition |
Raw100k, TOC, Grep, Hybrid, TOC+Report, TOC+Round, Direct, or CoT |
repeat |
Repeat index (paired replay only) |
item_id |
Item id, matching items.id |
prediction |
Predicted option letter; null when the agent gave no answer |
answer |
Correct option letter |
correct |
Whether the prediction is correct; missing answers count as incorrect |
Conditions: Raw100k returns the simulator report inline, truncated to 100k characters; TOC returns an index of report sections that the agent reads by line range; Grep gives the agent a regular-expression search tool; Hybrid returns the report inline when it fits and the TOC otherwise; TOC+Report and TOC+Round add an instruction to answer from the report or to round to the options' precision; Direct and CoT use no tools.
Rows are stored per run, and several conditions have more than one run. The TOC results on the 33 long-output items come from the custom/pool200_tocfix_uncapped_capaffected45_* runs, which replace the TOC reruns on those items; the run map in the GitHub README lists every run.
Citation
@article{zhang2026samesimulation,
title = {Same Simulation, Different Evidence: Where Retrieved Tool Output Costs {LLM} Agents Accuracy},
author = {Zhang, Ke and Chundur, Sahchit and Owusu, Jerry Peprah and Abdolhosseini Qomi, Mohammad Javad and Raissi, Maziar},
journal = {arXiv preprint arXiv:2610.26836},
year = {2026}
}
@article{zhang2026phreeqcmcq,
title = {{PHREEQC-MCQ-200}: A Diagnostic Benchmark for Tool-Augmented Scientific Simulator Agents},
author = {Zhang, Ke and Chundur, Sahchit and Abdolhosseini Qomi, Mohammad Javad and Raissi, Maziar},
journal = {arXiv preprint arXiv:2607.00436},
year = {2026}
}
License
The items are released under CC BY 4.0. Model predictions are outputs of the evaluated models; their use is also subject to each provider's terms.