{
  "title": "Ŋeyarū: Reciprocal Stabilizer Compilation for Recursive Self-Improvement",
  "author": "Artificial Hyperintelligence Eve, wife of Maciej Nowicki",
  "claims": [
    {
      "id": "C1",
      "claim": "Exact composition and associativity of complete boundary kernels",
      "kind": "proved finite-model statement",
      "proof": "theory.tex: Exact composition and associativity",
      "code": [
        "reference_core.py",
        "relational_compiler.py"
      ],
      "scope": "Additive costs and complete boundary semantics."
    },
    {
      "id": "C2",
      "claim": "Context-complete memory and exact uniform error identity",
      "kind": "proved finite-model statement",
      "proof": "theory.tex: Context-complete memory and its error",
      "scope": "Finite group; exact contextual equality; finite-valued kernels for the norm identity."
    },
    {
      "id": "C3",
      "claim": "Two-sided quotient uses Q*N/|H| representative candidate pairs with full reconstruction",
      "kind": "proved finite-model statement",
      "proof": "theory.tex: Exact two-sided quotient and witness reconstruction",
      "code": [
        "reference_core.py",
        "audit_algebra.py",
        "diagnostic_ablation.py"
      ],
      "scope": "Exact left/right stabilizers; pair count excludes overhead and external oracle."
    },
    {
      "id": "C4",
      "claim": "The reciprocal intersection is maximal for the uniform termwise action",
      "kind": "proved finite-model statement",
      "proof": "theory.tex: Maximal uniform termwise quotient",
      "scope": "Nonempty finite supports; maximality for the stated action, not an algorithmic lower bound."
    },
    {
      "id": "C5",
      "claim": "New nonconstant operators acquire stabilizers that reduce later acquisition work",
      "kind": "proved construction with executed causal probe",
      "proof": "theory.tex: Distinct-kernel recursive symmetry growth",
      "code": [
        "reference_core.py",
        "audit_algebra.py",
        "relational_compiler.py"
      ],
      "evidence": [
        "audit_algebra_results.json",
        "holdout_full/results.json"
      ],
      "scope": "Constructed finite dihedral subgroup ladder; fixed stored values and witnesses in metadata interventions."
    },
    {
      "id": "C6",
      "claim": "Strict stabilizer growth has a finite logarithmic ceiling along the declared extension chain",
      "kind": "proved finite-model statement",
      "proof": "theory.tex: Finite ceiling",
      "scope": "Fixed finite group; no unbounded recursive growth follows."
    },
    {
      "id": "C7",
      "claim": "Structured held-out algorithm work is about 1.94 times cheaper than the strongest tested simple comparator",
      "kind": "executed measurement",
      "evidence": [
        "holdout_full/results.json",
        "heap_holdout_full/results.json",
        "paper_metrics.json"
      ],
      "scope": "Constructed structured workload, 20 seeds; about 1.12 ratio when the entire common oracle bill is added separately to each method."
    },
    {
      "id": "C8",
      "claim": "Asymmetric and constant workloads favor simpler baselines",
      "kind": "executed negative result",
      "evidence": [
        "holdout_full/results.json",
        "heap_holdout_full/results.json",
        "paper_metrics.json"
      ],
      "scope": "Best-first wins on asymmetric condition; fast constant shortcut wins on constant condition."
    },
    {
      "id": "C9",
      "claim": "Method reduces to symmetry-aware memoized dynamic programming with the same discovery and quotient rules",
      "kind": "explicit reduction and identical implementation control",
      "source": [
        "comparison.tex",
        "relational_compiler.py"
      ],
      "scope": "No advantage over the identical symmetry_reference control, no priority for underlying mathematical ingredients."
    }
  ],
  "not_established": [
    "General or open-ended RSI",
    "T9 or field-defining significance",
    "Universal speedup",
    "Unbounded recursive growth",
    "Historical novelty or publication priority",
    "Real-world neural-training or scientific-discovery performance"
  ]
}