TypedPython: binary-trees is allocation-bound (1.7x); compiled New pays CPython's full alloc + GC tracking #125

Measured on PR #124 (interleaved, 11 pairs, load 9–13): binary-trees compiled is 1.7–1.8x CPython (both with __slots__), against 29–30x for nbody. The per-access class checks cost at most ~7% (within noise), so they are not the cause.

Hypothesis, not yet measured: each New goes through cls->tp_alloc (PyType_GenericAlloc: zeroing, GC header, PyObject_GC_Track), and dropping a tree runs subtype_dealloc with GC untrack and slot clearing. Compiled and interpreted code pay these alike, so they bound the speedup.

To do:

1. Profile compiled binary-trees, splitting time across alloc, dealloc, GC (gen-0 collections triggered by allocation count) and compiled code.
2. Only then consider options that keep CPython's observable behaviour, for example a per-type freelist or batching. Changing GC participation is observable (gc.get_objects, cycles), so it needs a decision.

Done when: the profile breakdown is posted and a decision is recorded on whether anything goes into M2b (2026-11-21).