pretty_name: SNO Article I Evidence
license: cc-by-4.0
language:
- en
tags:
- machine-learning
- reproducibility
- causal-analysis
- mnist
SNO Article I Evidence
Machine-readable experimental records supporting Watching Training Move: Causal Forecasting of Neural Updates Across 8,192 SGD Transitions.
Creator: TiGa-RCE
Affiliation: Independent researcher; founder and sole operator of Brewster Jennings
The Dataset contains original result records, figure-data contracts, and machine-readable receipts. It does not contain the article prose, the rendered figures, the source code, private conversations, local system paths, model caches, or downloaded MNIST data.
The long-horizon evidence includes a matched-runtime reproduction receipt for the exact PyTorch 2.13 result through 8,192 transitions and separately records the observed PyTorch 2.8 strict-hash portability boundary.
evidence/horizon/zerogpu-portability/ adds a bounded three-horizon control
comparing the local PyTorch 2.13 CPU path with a PyTorch 2.13 CUDA run on
Hugging Face ZeroGPU. Every recorded scientific decision agreed; blanket
numerical identity did not. The control is neither a full 8,192-transition
reproduction nor a CPU-versus-GPU performance benchmark.
License
Original Dataset material is licensed under the Creative Commons Attribution
4.0 International license. The complete terms are included in LICENSE and
are also available at https://creativecommons.org/licenses/by/4.0/.
Preferred attribution: “TiGa-RCE, independent researcher; founder and sole operator of Brewster Jennings.” Third-party identifiers and factual references are not relicensed by this Dataset.
Integrity
MANIFEST.sha256 binds every published Dataset file except the manifest
itself. The final HF Space must pin an exact Dataset commit rather than follow
the mutable main branch.
Status: public evidence Dataset. Publishing the Community Article remains a separate final gate.