docs(claude): note ptcna consolidation in prime-tensor stack cross-reference

CLAUDE.md

@@ -39,7 +39,7 @@ This file gives AI assistants (Claude Code and others) the context needed to wor
 
 **edcmbone** is a pip-installable Python library and monorepo implementing the **EDCM-PCNA-PCTA Framework** (Energy–Dissonance Circuit Model with Prime Circle Neural Architecture + Prime Circled Tensor Architecture). Its primary function is measuring structural fidelity loss in AI interactions — quantifying how much meaning an AI system deletes when transforming structured user input.
 
-> **Cross-reference — prime-tensor stack canon.** The canonical meaning and boundaries of the `PCNA` term (layer 1, **Prime Circle Neural Architecture**: tensors → circles in a back-propagating NN → weights) and the `PCTA` term (layer 2, **Prime Circled Tensor Architecture**: circles → seeds; repo `The-Interdependency/pcta`) live in `The-Interdependency/interdependent-lib : docs/prime-tensor-stack.md` — that role-and-boundary map is the source of truth, not this repo. The acronym expansions, the per-layer flow, and the variable-count rule (composition counts are variable; the only invariant is that every circle/seed/core is itself a tensor) were resolved by the maintainer on 2026-06-05. edcmbone is a measurement instrument that merely *names* these framework terms; consuming or naming PCNA / PCTA here transfers **none** of their (or UCNS-A's) theorem / proof / empirical status to EDCM, edcmbone, or UCNS-G (consistent with the UCNS-boundary non-transfer rule in `docs/ucns-boundary.md`).
+> **Cross-reference — prime-tensor stack canon.** The canonical meaning and boundaries of the `PCNA` term (layer 1, **Prime Circle Neural Architecture**: tensors → circles in a back-propagating NN → weights) and the `PCTA` term (layer 2, **Prime Circled Tensor Architecture**: circles → seeds) live in `The-Interdependency/interdependent-lib : docs/prime-tensor-stack.md` — since the 2026-07 consolidation those layers are the `neural`/`circle` and `seed` modules of the single **`ptcna`** package (`The-Interdependency/ptcna`; the former standalone `pcna`/`pcta`/`pcsa` repos are superseded) — that role-and-boundary map is the source of truth, not this repo. The acronym expansions, the per-layer flow, and the variable-count rule (composition counts are variable; the only invariant is that every circle/seed/core is itself a tensor) were resolved by the maintainer on 2026-06-05. edcmbone is a measurement instrument that merely *names* these framework terms; consuming or naming PCNA / PCTA here transfers **none** of their (or UCNS-A's) theorem / proof / empirical status to EDCM, edcmbone, or UCNS-G (consistent with the UCNS-boundary non-transfer rule in `docs/ucns-boundary.md`).
 
 **Status**: The repo-wide constant in `version.py` is `1.0.1`; the installable package (`backend/pyproject.toml`) declares `0.1.0` (Development Status: 3 - Alpha). The canonical, tested package lives under `backend/src/edcmbone/` and ships four working module groups (canon, parser, metrics, compress) plus `ucns/`. A root-level `edcmbone/` package and a `core/` framework package are an in-progress layer migration — mostly stubs or partial (see below).