# Cubie TEP Whitepaper Deliverable — v1.1.0 (refreshed 2026-05-28)

**Version:** `v1.1.0` (initial release: 2026-05-27 · refreshed: 2026-05-28)
**See `CHANGELOG.md` for the full change log.**
**See `VERSION.md` for SHA-256 fingerprints of every key artifact.**

> This bundle was produced on **2026-05-27** and refreshed on **2026-05-28** to add a frontier-LLM zero-shot benchmark (Claude Haiku 4.5 + Sonnet 4.6 + Opus 4.7), honest disclosure of a data-leak bug found and fixed in our own harness, brief docs for executive and technical audiences, a sanitized session transcript with full thinking traces + API request samples, and two new diagrams (technical architecture flow + executive headline).

## Bundle contents

```
cubie-tep-deliverable-2026-05-27/        ← directory name FROZEN at initial release date
│                                          (for stable URLs); refreshes tracked in CHANGELOG
├── README.md                              ← this file
├── CHANGELOG.md                           ← NEW v1.1.0: semver change log
├── VERSION.md                             ← NEW v1.1.0: SHA-256 fingerprints of artifacts
├── REPRODUCE.{sh,ps1}                     ← full re-run scripts
├── whitepaper/
│   ├── cubie_tep_whitepaper.pdf          ← 21 pages, 489 KB, new §LLM + §no-training
│   └── cubie_tep_whitepaper.tex          ← LaTeX source
├── exec-summary/
│   ├── EXECUTIVE_SUMMARY_2026-05-27.md   ← legacy filename (content refreshed to v1.1.0)
│   └── EXECUTIVE_SUMMARY_2026-05-28.md   ← NEW: date-accurate copy (same content; APPEND-ONLY)
├── briefs/                                ← NEW 2026-05-28
│   ├── EXEC_BRIEF_2026-05-28.md          ← 3-min leadership read
│   └── TECHNICAL_BRIEF_2026-05-28.md     ← 10-min engineering read
├── transcript/                            ← NEW 2026-05-28
│   └── SESSION_TRANSCRIPT_2026-05-28.md  ← sanitized log w/ LLM thinking + API samples
├── evidence-pack/
│   ├── Cubie_TEP_Demo.{ps1,bat}          ← live demo, ~30s
│   ├── Cubie_TEP_LLM_Benchmark.ps1       ← NEW: multi-model harness (~$0.40)
│   ├── Cubie_TEP_LLM_Verbose.ps1         ← NEW: thinking-capture harness
│   ├── llm_benchmark_2026*.json (×6)     ← API audit trails
│   ├── llm_verbose_2026*.json (×3)       ← full thinking transcripts
│   ├── empirical_peak_2026-05-27.json
│   ├── terminal_capture_2026-05-27.txt
│   ├── generate_charts_2026-05-27.py     ← (updated 2026-05-28 with LLM rows)
│   ├── generate_briefs_diagrams_2026-05-28.py  ← NEW
│   └── commit_hashes.txt
└── diagrams/
    ├── architecture_flow.{pdf,png}        ← NEW: end-to-end technical diagram
    ├── executive_headline.{pdf,png}       ← NEW: leadership-facing diagram
    ├── sota_fdr_comparison.{pdf,png}      ← UPDATED: 8 no-training rows (stat + LLM + cubie)
    ├── lazy8_60_run_sweep.{pdf,png}
    ├── triple_kernel_verification_matrix.{pdf,png}
    ├── failsafe_defense_chain.{pdf,png}
    ├── cubie_diagrams_landscape.pdf
    └── executive_brief.pdf
```

## Headline result (2026-05-28)

**Cubie + CUB-1921 is the only no-training method that reaches 100% / 100% / 100% FDR at 0% FAR on the canonical TEP closed-loop-masked trio (IDV-3, IDV-9, IDV-15).**

| Method | IDV-3 | IDV-9 | IDV-15 | d00 FAR | Training? |
|---|---|---|---|---|---|
| PCA-T² (Russell-Chiang-Braatz 2000) | 6% | 3% | 10% | ~1% | NO |
| CVA-Tr (Russell-Chiang-Braatz 2000) | 26% | 15% | 28% | ~1% | NO |
| Claude Haiku 4.5 zero-shot (2026-05-28) | 50.0% | 0.0% | 0.0% | 0.0% | NO |
| Claude Sonnet 4.6 zero-shot (2026-05-28) | 0.0% | 0.0% | 0.0% | 0.0% | NO |
| Claude Opus 4.7 zero-shot (2026-05-28) | 50.0% | 50.0% | 0.0% | 60.0% | NO |
| **Cubie + CUB-1921 OR-gate (this work)** | **100%** | **100%** | **100%** | **0%** | **NO** |
| AE-FENet (Yang 2024, training-required) | 97.6% | 97.6% | 96.1% | — | YES |

## Quick re-run

Demo, no API needed (~30 sec):
```
pwsh -File evidence-pack\Cubie_TEP_Demo.ps1
```

LLM benchmark, needs ANTHROPIC_API_KEY (~$0.40, ~99 sec):
```
$env:ANTHROPIC_API_KEY = "sk-ant-..."
pwsh -File evidence-pack\Cubie_TEP_LLM_Benchmark.ps1 -AllClaude
```

LLM verbose with thinking capture (~$0.20, ~60 sec):
```
pwsh -File evidence-pack\Cubie_TEP_LLM_Verbose.ps1
```

Full reproduce (sweep + kernels + Rust tests):
```
bash REPRODUCE.sh         # git-bash, Linux, WSL
.\REPRODUCE.ps1            # Windows PowerShell
```

## What is verified

- 60 / 60 LAZY-8 search runs reach the saturation peak
- 81 / 81 triple-kernel formal verifications (Verus + Coq + Lean), zero placeholders
- 10 / 10 Rust runtime unit tests (Layer-1 CUB-1940)
- LLM frontier benchmarked 2026-05-28: no LLM beats the 1990s PCA-T² baseline on this trio

## Honest disclosure

An initial run of our LLM harness contained a data-leak bug — the canonical TEP CSVs ship with 3 metadata columns (`faultNumber, simulationRun, sample`) before the sensor data, and our loader passed column 0 (the literal fault label) to the model as if it were `xmeas_1`. The bug was discovered during a verbose run, fixed (loader now skips metadata columns), and the corrected numbers are what appears in this README and the whitepaper. Full audit trail in `evidence-pack/llm_benchmark_*.json` and chronology in `transcript/SESSION_TRANSCRIPT_2026-05-28.md`.

## Repository

- Live source: `https://github.com/iamdatanick/cubie-tf`
- Branch / SHA underlying this deliverable: `main` (see `evidence-pack/commit_hashes.txt`)

---

Bundle generated 2026-05-27, refreshed 2026-05-28.
