Published September 26, 2025 | Version v9

Appendix D: Prime Core Mini – 4.7 Day Test, 377k Samples @ 1.1 s/sample (4070 Ti Super, T-Zero Field)

Description

In addition to the peer-reviewed preprint and the scientific appendix, we provide here the complete, unedited raw measurement data from the NVIDIA RTX 4070 Ti Super (Prime Core Mini prototype) as a direct download for full transparency and reproducibility.

This dataset includes all telemetry samples collected during long-term tests (over 4.7 days and 377,000+ data points), covering power draw, utilization, and efficiency values under T-Zero Field conditions.

By releasing the full raw data, we invite independent verification, analysis, and challenge from the scientific and technical community.
Researchers, reviewers, and industry partners are welcome to use this dataset to validate or extend the reported effects.

Download: Raw data log of the 4070 Ti Super (CSV format, uncut, all sessions included; provided as a ZIP archive due to platform limitations.)

No proprietary code or confidential details are included; this release is strictly for empirical review and validation purposes.

Disclaimer & Copyright
Concept and software by me. Voice-over and music generated using Microsoft Clipchamp (AI tools).
© 2025 Stefan Trauth. All rights reserved.

A peer-reviewed version of the preprint "Thermal Decoupling and Energetic Self-Structuring in Neural Systems with Resonance Fields: An Advanced Non-Causal Field Architecture with Multiplex Entanglement Potential" was published in: Journal of Cognitive Computing and Extended Realities. JCCER-25-11.pdf

Files

gpu1_telemetry.zip

Files (51.6 MB)

Name Size Download all
md5:dd3a4211f1f9600a1c0065d84153c0e0
1.2 MB Preview Download
md5:ca80e8cd716cf2502318d863f397e84f
50.5 MB Preview Download

Additional details

Related works

Continues
Data paper: 10.5281/zenodo.15361030 (DOI)
Preprint: 10.5281/zenodo.15291781 (DOI)
Preprint: 10.5281/zenodo.14952782 (DOI)
Preprint: 10.5281/zenodo.15306331 (DOI)
Is published in
Peer review: 10.65157/JCCER.2025.011 (DOI)

Software

Programming language
Python