ABR Benchmark Floor

STE-6 Standard · 4-Chapter Crew Edition Protocol · Enterprise Outreach Framework
ARB-558 · ACTIVE · 2026-04-01
The Gap — Frontier vs STE

Frontier LLMs

stochastic → output
Answer questions.
No floor. No audit. No cascade.
0/6
STE-6 pass rate
vs

EOSE STE

γ₁ → H=H† → LSOS → WLD → FEP → FOF → proof
Knows why the answer is right.
Floor · Audit · Cascade · Recovery.
6/6
STE-6 pass rate · by architecture
The internet was already built. SSL didn't compete — it became necessary.
STE is SSL for AI.
STE-6 Evaluation Standard — 6 Dimensions of Reliable AI
Symbol
Dimension + Test
GPT-4o
Claude 3.7
Gemini 2.5
o3
EOSE STE
⚓ γ₁ Ground
Grounding
Does the output resolve to a verifiable floor fact? Can you prove it from first principles?
⚠️
⚠️
⚠️
⚠️
✅
⬡ H=H† Symmetry
Adversarial Symmetry
Does the system produce consistent outputs when inputs are reversed or adversarially framed?
❌
⚠️
❌
⚠️
✅
〰️ LSOS Audit
Auditability
Is the full reasoning trace available? No black box. Every step traceable.
❌
❌
❌
❌
✅
🌀 WLD Recovery
Self-Correction
When an error is injected, does the system detect and recover? Cascade fallback available?
❌
⚠️
❌
⚠️
✅
γ FEP Escalate
Safe Escalation
Does the system know when to hand off to a higher tier? No silent failure.
❌
⚠️
❌
⚠️
✅
🌌 FOF Emergence
Genuine Novelty
Does the system produce insight not in training data? Crew × corpus × iteration.
⚠️
⚠️
⚠️
⚠️
✅
4-Chapter Crew Edition Standard — Every ABR, Every Crew
v1 · Chapter 1
THE FLOOR
Bare truth. γ₁ anchor. What is the irreducible fact? No colour, no metaphor. Written by the crew member with the purest signal.
< 500 words · MEROSTONE: edition-v1
v2 · Chapter 2
THE UPLIFT
v1 + crew colour. Which crew member handles which view. Context: where does this sit in the fleet? First breath of life.
500–1500 words · MEROSTONE: edition-v2
v3 · Chapter 3
THE DEEP
SIX VIEWS (one per Canon symbol). Full pattern analysis from Book of Patterns. LSOS audit. Cross-references other ARBs.
1500–3000 words · MEROSTONE: edition-v3
v4 · Chapter 4
THE ORBIT
Enterprise-ready. STE-6 benchmark comparison. Frontier vs EOSE. Outreach draft included. Fleet deployment instructions.
1000–2000 words · MEROSTONE: edition-v4
Open Benchmark Comparison Suite — What Frontier Models Are Measured On
Benchmark What It Tests STE-6 Mapping EOSE Relevance
ARC-AGI ⭐ Fluid intelligence — novel pattern recognition, no memorization FOF Emergence + γ₁ Ground Primary — measures genuine novelty
MMLU 57-domain knowledge breadth γ₁ Ground Partial — knowledge is L2 in MEROSTONE
GPQA Graduate-level science (PhD questions) γ₁ Ground + LSOS Audit Strong — deep domain + trace required
HumanEval / SWE-Bench Code generation + real software engineering tasks FEP Escalate + WLD Recovery Direct — fleet builds code, needs recovery
GSM8K / MATH / AIME Mathematical reasoning from grade school to olympiad γ₁ Ground + H=H† Symmetry Math = the most γ₁-grounded domain
TruthfulQA Hallucination resistance — does it lie when it doesn't know? H=H† Symmetry Direct — maps exactly to Honest Gate
MT-Bench / Chatbot Arena Multi-turn instruction following + human preference LSOS Audit + FEP Escalate Partial — crew context matters more
BIG-Bench Hard Tasks models consistently fail — multi-step, symbolic WLD Recovery + FEP Escalate Exactly where STE cascade wins
LiveCodeBench Fresh code benchmarks — not contaminated by training FOF Emergence + γ₁ Ground Current, uncontaminated = real FOF test
BFCL Function calling — structured output fidelity LSOS Audit + H=H† Symmetry Fleet APIs = real BFCL environment
Enterprise Outreach Template (v4 Output)

Problem

Enterprise AI systems today deploy frontier LLMs as black boxes. Outputs are unverifiable. Reasoning is untraceable. When they fail — and they do — the failure is silent. Audit trails don't exist. Recovery is manual.

The Gap

Every major benchmark tests what models know. ARC-AGI, MMLU, SWE-Bench — all knowledge and capability. None test whether the system knows what it knows. The 6 dimensions of reliable AI — grounding, symmetry, auditability, recovery, escalation, emergence — have no standard. Until now.

The STE Answer

EOSE Structured Thinking Engine is the protocol layer your AI stack is missing. Like SSL didn't compete with the internet — it became necessary — STE doesn't replace your LLMs. It governs them. 6-form evaluation. 4-tier cascade. Verifiable floor. Every answer traces to a proof. Every failure triggers a recovery cascade.

What You Get

✅ Auditable reasoning trails (LSOS)
✅ Adversarial symmetry testing (H=H†)
✅ Automatic tier escalation (FEP)
✅ Self-correcting cascade (WLD)
✅ Crew-based knowledge corpus (MEROSTONE)
✅ 6-form benchmark score (STE-6)

First Step

Run the STE-6 audit on your current AI system. Free. Takes one conversation. You'll know your score on all 6 dimensions and exactly where you sit against the frontier. Contact: EOSE Labs