KLM

KLM (Knowledge Layer Model) is an open, implementation-neutral specification for defining inference records, which contain versioned epistemic assessments, evidence relations, and explicit unknowns.

In a historical platform-domain routing benchmark, the system completed 137/150 correct classifications across 15 categories, for an accuracy of 91.3%, with a nominal 95% Wilson interval of 85.7-94.9%.

The numerator of the above routing diagnostic benchmark was recovered from a rounded summary, and the attribution of the historical samples has not been verified, so the 91.3% accuracy carries uncertainty and cannot be cited directly as a precise performance metric.

In the corrected two-source test, the native model weight path configuration had 0/15 successful answers.

The capacity growth comparison could not establish a reliable effect because the legacy scorer was flawed and the original outputs were missing.

In legacy packing, 118/221 selected cases lost content containing the gold-standard text; the fixed packing retained this text in 221/221 cases, but this measures text presence rather than answer quality.

The Python and TypeScript validators reportedly agree on six checks per synthetic fixture suite, but an independent production disclosure was not accepted.

Recovery, re-derivation, human rubric support, boundary isolation, and bounded response evaluation remain at the proposal stage.

The authors emphasize that evidence visibility does not establish correctness, causal dependence, safety, or regulatory compliance; independent reproduction and a complete public audit package remain future work.