Freeze before grade
Treatment identity is separated from the grading surface and replacements/missing observations are recorded rather than silently dropped.
The research program follows mechanisms across product development without turning implementation progress into scientific conclusions. Negative and mixed results remain visible because they often identify the next experiment more clearly than a forced winner.
The latest accepted controlled study asks whether actionable corrective feedback improves required authorized movement while preserving restraint, carried state and output quality.
The completed experimental series now totals 576 model generations, 288 canonical blind machine grades, and 72 assisted H1 calibration cases across three independently frozen rounds. Those totals describe research volume; they are not pooled into one synthetic efficacy estimate.
Full-48 machine quality B−A was −0.03125 with paired bootstrap 95% CI [−0.2604, +0.1875]. The tested treatment did not establish an aggregate quality advantage or aggregate governance improvement.
Across the broader required-signal seam, 4 of 11 cases were repaired and 7 remained unresolved. Three cases also lost a blocked-use boundary without authority. The current mechanism thesis is therefore narrower: detection validity, repair-target specificity, collateral preservation and independent acceptance are separable.
The program uses matched boundaries, blind treatment mapping, versioned graders, explicit missing/replacement handling, paired uncertainty, human/machine discordance review and claim ceilings that survive a positive-looking result.
Treatment identity is separated from the grading surface and replacements/missing observations are recorded rather than silently dropped.
Paired bootstrap intervals and exact win/tie/loss or discordance summaries are used where the design supports them; decorative math is not the goal.
Each completed round used a separately frozen 24-case H1 assisted-calibration body. The cumulative 72 cases remain explicitly classified as user-cosigned, multi-machine-assisted evidence—not unaided independent human validation.
Parser, runtime, scorer, evaluator and protocol failures are separated from product behavior so the instrument itself cannot silently become the result.
These are research work products and manuscript states, not claims of publication or peer review.
Required movement, restraint, carry, and the boundary between a valid deterministic signal and an authority-bounded repair.
Evaluation infrastructure, construct validity, protocol-preserving repair, and what remains scientifically interpretable after the evaluator breaks.
Quality-per-compute, latency, token use and human correction burden. Held until exact compute evidence is captured.
Cross-domain testing across logistics, physical assets, disaster risk and real-estate state without treating shared architecture as proof of generalization.
Human/machine calibration, exact-state semantic disagreement and the limits of using model judges as claim multipliers.
This section is wired for simple future updates. Public PDFs can be added without redesigning the page; the core research narrative above remains static and crawlable.
External research threads, release notes, conference posts and public commentary can be linked here as they are published.
Kingan Logic is open to bounded research collaboration, independent replication and evaluation relationships where the protocol, evidence and contribution can be stated clearly.