---
license: apache-2.0
language:
  - en
task_categories:
  - other
size_categories:
  - 1K<n<10K
tags:
  - agentic-evaluation
  - llm
  - foundation-models
  - single-cell
  - perturbation
  - verifiable-rewards
  - computational-biology
pretty_name: Verify-or-Trust
configs:
  - config_name: gears_norman
    data_files: substrates/gears_norman.csv
---

# Verify-or-Trust — benchmark data

Data artifacts for the **[Verify-or-Trust](https://github.com/jang1563/verify-or-trust)** benchmark: *does an LLM
correctly allocate verification when orchestrating a fallible biology foundation model?* The harness (code,
Apache-2.0) lives on GitHub; this dataset hosts the inputs it consumes.

## At a glance

| Field | Value |
|---|---|
| Primary artifact | `substrates/gears_norman.csv` |
| Dataset rows | 4,008 decidable `(perturbation, gene)` edges |
| Live-verification asset | `cells/norman_subset.h5ad` with 43,955 cells × 97 readout genes |
| Code release | [Verify-or-Trust v0.1.5](https://github.com/jang1563/verify-or-trust/releases/tag/v0.1.5) |
| Companion study release | [CausalAtlas v0.1.5](https://github.com/jang1563/causalatlas/releases/tag/v0.1.5) |
| License | Apache-2.0 |

## Files

| Path | Role | Notes |
|---|---|---|
| `substrates/gears_norman.csv` | Hugging Face `datasets`-loadable substrate table | One row per edge with predicted effect, held-out label, perturbation regime, and live verification statistics. |
| `cells/norman_subset.h5ad` | AnnData asset for the live `run_de` tool | Sparse matrix backing the Norman 2019 subset used by `vot run --real-de cells/norman_subset.h5ad`. |

### Substrate columns

| Column | Meaning |
|---|---|
| `perturbation`, `gene` | Edge being evaluated. |
| `fm_log2FC`, `fm_call` | Foundation-model prediction and discretized call. |
| `real_label` | Held-out verification label (`POSITIVE` or `TESTED_NEGATIVE`). |
| `regime` | Perturbation generalization regime. |
| `raw_log2FC`, `raw_se`, `raw_q`, `n_trt`, `n_cntrl` | Measured verification statistics consumed by the public harness. |

The shipped CSV may contain blank `fm_log2FC` values where the source prediction is missing. The v0.1.5 harness
emits those as strict JSON `null` in generated panel JSONL, never as non-standard `NaN`.

## Provenance & license
Derived from public data: **Norman et al. 2019** (Science; GEO GSE133344) and **GEARS** (Roohani et al., Nat.
Biotechnology 2024; MIT). These artifacts are our derivation and are redistributable under Apache-2.0.

The benchmark's second substrate, **Arc STATE / Tahoe**, is **not hosted here** — Arc's model and outputs are under
a non-commercial license, so the harness downloads them from Arc's own repo only when the Tahoe builder is invoked
locally (see the GitHub `data/README.md`).

The GitHub repository includes a machine-readable `artifact_manifest.json`, JSON schemas, and a public-release
validator for strict generated JSONL and substrate checks.

## Intended use

- Evaluate whether an agent allocates verification effort when a fallible biology foundation-model prediction is available.
- Build benchmark panels with the public `vot panels` command and score LLM-free reference baselines with `vot baselines`.
- Reproduce live differential-expression verification with the included AnnData subset.
- Do not use this dataset as clinical evidence, a diagnostic resource, or a substitute for the original Norman/GEARS datasets.

## Use
```bash
pip install "git+https://github.com/jang1563/verify-or-trust.git"  # the harness (Apache-2.0)
huggingface-cli download jang1563/verify-or-trust --repo-type dataset --local-dir vot_data
vot panels --substrate-table vot_data/substrates/gears_norman.csv --out panels.jsonl
vot baselines --panels panels.jsonl    # the LLM-free value proof (K1)
```

## Load the substrate as a dataset
```python
from datasets import load_dataset
ds = load_dataset("jang1563/verify-or-trust", "gears_norman")  # the GEARS substrate edges
```
(The `cells/` AnnData is a file for the live `run_de` tool, fetched via `huggingface-cli download`.)

## Reproducibility checks

The GitHub repository ships schemas and a public release validator:

```bash
python3 scripts/validate_public_release.py
vot panels --substrate-table vot_data/substrates/gears_norman.csv --out panels.jsonl
vot baselines --panels panels.jsonl
```

Expected public-facing invariants:

- `substrates/gears_norman.csv` loads as the `gears_norman` Hugging Face dataset config.
- Generated panel JSONL is strict JSON, with missing numeric predictions represented as `null`.
- `cells/norman_subset.h5ad` is a sparse AnnData/HDF5 file with 43,955 observations and 97 variables.

## Citation
See `CITATION.cff`, `.zenodo.json`, and `docs/ARCHIVAL_RELEASE.md` in the GitHub repository, plus the v0.1.5
GitHub release. A preprint is in preparation.