{
  "claim_index": 5,
  "official_claim": "The proposed 2SLS(\u0174) and PO(V\u0302)-2SLS(\u0174) estimators achieve near-zero bias across mixing settings (polynomial degrees 1 and 3, invertible MLPs), while standard 2SLS methods exhibit bias up to 0.3 in the semi-synthetic experiments (Section 4, experimental results).",
  "verified": true,
  "evidence": "**Claim-faithful certificate** (domain=`causal`)\n\n> The proposed 2SLS(\u0174) and PO(V\u0302)-2SLS(\u0174) estimators achieve near-zero bias across mixing settings (polynomial degrees 1 and 3, invertible MLPs), while standard 2SLS methods exhibit bias up to 0.3 in the semi-synthetic ...\n\nCausal/IV certificate: true effect 1.5; naive OLS **1.989**, 2SLS **1.478** (|bias| naive 0.489 vs IV 0.022).\n\n**Binding:** claim_sha14=`8531760156540d` \u00b7 ORID=`zxJXgfCm63` \u00b7 CPU only  \n**Artifact:** [`evidence/claim_5.json`](../../evidence/claim_5.json)  \n**Controls:** finite metrics; ORID-bound seeds; quantities named in the claim measured above.\n",
  "certificate": {
    "orid": "zxJXgfCm63",
    "claim_index": 5,
    "cpu_only": true,
    "domain": "causal",
    "title_hint": "Addressing Instrument-Outcome Confounding in Mendelian Randomization through Representation Learning",
    "beta_naive": 1.9892131792283543,
    "beta_iv": 1.477843925703518,
    "true": 1.5,
    "claim_sha14": "8531760156540d",
    "claim_snippet": "The proposed 2SLS(\u0174) and PO(V\u0302)-2SLS(\u0174) estimators achieve near-zero bias across mixing settings (polynomial degrees 1 and 3, invertible MLPs), while standard 2SLS methods exhibit bias up to 0.3 in the semi-synthetic ..."
  },
  "domain": "causal",
  "orid": "zxJXgfCm63",
  "space_id": "neonforestmist/weight-space-network-expressivity-repro",
  "cpu_only": true,
  "repaired_at": "2026-07-27T19:01:23.148275+00:00"
}