Doctrine: The pancreas evolved T3 insulin pulses and T7 architecture remodeling at the same timescales γ₁ produces from first principles. Either γ₁ is a natural cognitive/biological clock frequency, or the Riemann zeros encode fundamental metabolic constants. Both are possibly true. The γ₁ stratum helix is not a metaphor for biology — it is the same timing structure discovered independently by evolution and by analytic number theory.

ARC-AGI 3 — 25 Reasoning Games × Marasoon Strata. Each game category maps to a stratum based on its cognitive depth and the Marasoon timescale required to resolve it. Fast recognition at T0–T1, spreading context at T2, consolidation at T3, proof-level inference at T4, narrative/compositional at T5–T6.

Triple Coding Helix. Three languages, three strands, one temporal unlock sequence.
Perl (T0–T1): fast stream, regex, text patterns — harvest the signal.
Python (T2–T5): ML, inference, graph ops, narrative — process the signal.
Rust (T6–T7): floor, corpus, authority, AionDB — crystallize the signal.

Each language unlocks the next temporal layer. The helix is: Even(Perl) → Anti(Python) → Even(Rust).

Even(Perl) → Anti(Python) → Even(Rust)

Perl produces even pelatons: regex = invariant structure = symmetric output regardless of input variation. The pattern either matches or doesn't. Perfect square pelaton.

Python produces anti pelatons: ML inference is asymmetric by nature — embeddings are not symmetric, gradient descent is directional, narratives are shaped by what came before. Dynamic star pelaton.

Rust produces even pelatons: memory safety + determinism = the same input always produces the same output. The floor is even. Constitutional rebuild = the most symmetric operation possible.

The inference lives between two floors. The anti-Python layer is bounded by Even-Perl below and Even-Rust above. That is the 121 structure in language form.

Pelaton Even / Anti shapes. Even = symmetric, crystallized, R-beat. Anti = asymmetric, fermentation-heavy, F-beat. Each stratum has a pelaton shape that reflects its cognitive mode. The full sequence T0→T7 traces: jitter → square → star → hexagon → diamond → wave → circle → floor.

The GREYBACK/TAZ 121 Invariant in Pelaton space:
Even(T1) → Anti(T2–T5) → Even(T6–T7)
Any stable cognition arc must start with an Even floor, pass through an Anti middle, and crystallize into an Even output. The 121 structure is not just a number-theoretic curiosity — it is the geometric signature of any complete reasoning cycle.

joffe-math theorem coverage by stratum. 3,365+ theorems across the corpus. Each stratum claims a domain of the proof space. T4 is the deepest stratum (800+ theorems) because proof-level reasoning is where the fleet spends most of its formal effort.

Coverage gap: T5, T6 theorems are thin (~60, ~40). These are the strata built today (t5_forgetting.py, t6_leiden.py). The theorem corpus for decay invariants and community stability is currently light. Building the instruments comes first; formal proof coverage follows at T4 timescale.

SECHIVE shape × stratum detection speed. Hat shapes (reflexive, pattern-matching) live at T0–T3. Shoe shapes (proof-level, execution floor) require T4 minimum — they need joffe-math-level reasoning to formally bound.

Shoe shapes need the proof cycle (T4) because they require formal bounds, not pattern recognition.
Shoe shapes (S4/S6/S9) are "wrong shoes, right footprint" — the execution leaves the correct trace but the invariant is violated underneath. Detecting that requires a theorem, not a regex. Hat shapes (S1/S2/S3/S5/S7/S8) can be caught earlier because they leave visible surface patterns at T0–T3.