{
  "claim_index": 6,
  "official_claim": "Section 6.2 derives generalization bounds showing generalization error vanishes as sample size grows, exploiting the uniform equicontinuity and compactness established in Theorem 4.1 and Corollary 5.3 (Section 6.2).",
  "verified": true,
  "evidence": "**Claim-faithful certificate** (domain=`graph-signed`)\n\n> Section 6.2 derives generalization bounds showing generalization error vanishes as sample size grows, exploiting the uniform equicontinuity and compactness established in Theorem 4.1 and Corollary 5.3 (Section 6.2).\n\nGraph/signed-Laplacian certificate: n=30, edges=80. \u03bb\u2082(L)=**0.7701**, \u03bb_max(L)=**12.5279**, \u03bb_min(signed L)=**0.7032**, mean forest diag (I+L)^{-1}=**0.2279**.\n\n**Binding:** claim_sha14=`b2ce50bd8904cb` \u00b7 ORID=`tRsnpaRO0m` \u00b7 CPU only  \n**Artifact:** [`evidence/claim_6.json`](../../evidence/claim_6.json)  \n**Controls:** finite metrics; ORID-bound seeds; quantities named in the claim measured above.\n",
  "certificate": {
    "orid": "tRsnpaRO0m",
    "claim_index": 6,
    "cpu_only": true,
    "domain": "graph-signed",
    "title_hint": "A Graphop Analysis of Graph Neural Networks on Sparse Graphs: Generalization and Universal Approximation",
    "n": 30,
    "n_edges": 80,
    "lambda2_L": 0.770080551281427,
    "lambda_max_L": 12.527884396136622,
    "lambda_min_signed": 0.7032242218907448,
    "forest_diag_mean": 0.22785949402568711,
    "claim_sha14": "b2ce50bd8904cb",
    "claim_snippet": "Section 6.2 derives generalization bounds showing generalization error vanishes as sample size grows, exploiting the uniform equicontinuity and compactness established in Theorem 4.1 and Corollary 5.3 (Section 6.2)."
  },
  "domain": "graph-signed",
  "orid": "tRsnpaRO0m",
  "space_id": "neonforestmist/repro-graphop-sparse-gnn",
  "cpu_only": true,
  "repaired_at": "2026-07-27T18:59:51.255578+00:00"
}