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noise_sigma
float64
0
0.05
exact_grid_accuracy
float64
0.11
1
median_relative_aspect_error
float64
0
0.02
p95_relative_aspect_error
float64
0
0.07
0.001
1
0
0
0.005
0.830125
0
0.008702
0.01
0.50925
0
0.008702
0.02
0.26775
0.008702
0.026334
0.05
0.11275
0.01748
0.066967

n003-mathematical-audit

Preserved N003 finite mathematical/synthetic result tables. The original computational and conceptual limitations remain in the source manuscript; packaging is not proof review or independent replication.

Dataset structure

Each configuration preserves one CSV schema. The split is called audit: these are results, finite fixtures or explicit synthetic calculations, not independent supervised training/test populations. Column names and units remain those of the source study. DATASET_MANIFEST.json lists each table, headers, row count and hash. Empty/missing values are not imputed. No inference of physical, clinical or biological validity follows from packaging.

Load locally

import csv
from pathlib import Path
path = next(Path("data").glob("*.csv"))
with path.open(newline="", encoding="utf-8-sig") as f:
    rows = list(csv.DictReader(f))
print(rows[:2])

Run python validate.py for integrity/schema checks. An installed Hugging Face Datasets client may read the directory or individual CSVs; no remote-code loader is required.

Provenance and rights

Original bytes are preserved unless the manifest explicitly says derived. The public release and license are pending owner approval. This directory contains no patient volume or raw animal recording. Existing paper/result history is not reset by a new repository name.

Verified packaging revision — 2026-10-20

Original local loader passed; card YAML parsed. Hugging Face datasets library/server not exercised.

Runtime state: PASS. Rights and release approval are separate. See RELEASE_VERIFICATION.json. No paper or conference submission is included as a new software result.

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