Claim-Evidence Ledger

Every material public claim about mixle, with the strongest evidence that currently supports it. The point of a credibility release is that claims are graded, not asserted: a reader can see exactly how far each statement has been verified and decide whether that is enough for their use.

Evidence grades (from the 0.8.0 release contract):

• E0 — assertion: prose, design intent, or a unit test with a stand-in only.

• E1 — local correctness: a deterministic unit/integration test on one machine.

• E2 — artifact correctness: a test from a clean installation of the built wheel.

• E3 — realistic workload: real public data, or a real external model/backend, at bounded scale.

• E4 — independent reproduction: another environment or person reproduces it from documented steps.

• E5 — production/scale: sustained real deployment, or representative multi-node/multi-GPU runs.

Stable-core claims target at least E2; performance and backend claims target at least E3. “Production-ready”, “safe”, or “frontier” claims require E5 and are not made in 0.8.2. Grades here are the release owner’s current assessment and are revised as evidence lands (several are pending the exact-tip re-run for this release, marked below).

Claim	Grade	Evidence / caveat
~90 distribution families with a common estimator/sampler/encoder contract	E1	Source-tree family, sampler-seed, and scipy-golden density tests cover the broad provisional catalog. A clean-wheel import sweep is not behavioral evidence for every family.
Seven stable scalar families satisfy normalization, score, fit, and serialization invariants	E2	The exact wheel is installed into an isolated environment; the stable invariant catalog runs there with no source-tree import path and retains JUnit evidence.
“15,000+ tests”	E1	Measured 2026-09-08: 16,849 collected (pytest --collect-only -m "") on the 0.8.2 candidate. The tiers run in CI (core on 3.11–3.12 and both platforms, full sharded on 3.12, optional sharded); not yet run from the wheel for the whole suite (only the import sweep is) — that remains an exit criterion for this release too, unchanged from 0.8.1.
One optimize(...) call fits a heterogeneous composed base model	E2	The collection-light public fit path runs from the isolated installed wheel and retains JUnit evidence. Neural and latent compositions remain E1 unless their optional installed-wheel lane is retained separately.
A PyTorch module fits in one line with parity to a hand-written loop	E1	torch_parity_test / grad_control_test check parity, freezing, and checkpointing (torch extra).
Distillation into a small local model with calibrated deferral and a cost/quality receipt	E1	Task/calibration/cascade tests are E1 on synthetic teachers. The repository carries no direct dataset usage (2026-08-04 decision), so real-data task evidence lives in notebooks outside it and is not claimed here.
HMM / GMM performance and crossover behavior	none	The harness is tracked in benchmarks/. Older measurements are archived and are not release evidence; numbers may be published only after an exact-candidate retained run.
Distributed estimation over Spark / Dask / Ray / MPI by switching one argument	E1	Per-backend encoded-data tests exist. Dask and torchrun are exercised in the scheduled optional lane; Spark, Ray, MPI, and Lightning remain tested locally but not CI-gated. Wording is qualified in the backend support matrix.
Distributed transformer and MoE training	E1	The native backend executes DDP/FSDP2/HSDP and selected TP/CP paths; Megatron Bridge owns full TP/PP/CP/EP/ETP. CPU objective/checkpoint and provider-delegation tests establish local correctness, not a realistic-scale run. GPU throughput, MFU, and multi-node recovery remain unverified until retained hardware receipts exist. Unsupported axes fail capability validation.
Serialization round-trips and provenance / replay	E1	Fresh-process serialization tests; lineage/receipt tamper-and-replay tests. Cross-version (load a prior release’s artifact) fixtures: digest-bound 0.7.0 load fixtures for the stable persistence schemas exist (see The Stable Surface); broader cross-version coverage remains a 0.8.1 gate (worklist M11.2).
Calibrated abstention (conformal / cascade / escalation)	E1	Conformal-coverage and calibration-diagnostic tests. This is a deferral mechanism, not a safety guarantee — no “safe to deploy” claim is made (needs E5).

This ledger is maintained alongside the release checklist; when a claim’s evidence changes, update the grade in the same change.