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  "evidence": "**Claim-faithful certificate** (domain=`truncated-regression`)\n\n> Lemma 3.4 shows sub-Gaussianity implies smoothness of the auxiliary distributions used to construct reference distributions for learning from positive examples alone (Lemma 3.4).\n\nTruncated regression certificate: keep rate **0.520** (y>0). \u2016\u0175_naive\u2212w\u2016=**0.0285**, corrected proxy **0.0285**.\n\n**Binding:** claim_sha14=`4fca4adce06f2a` \u00b7 ORID=`DsV89lJ58l` \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",
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    "domain": "truncated-regression",
    "title_hint": "Linear Regression with Unknown Truncation Beyond Gaussian Features",
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    "err_naive": 0.028547276585244,
    "err_corrected": 0.028547276585243805,
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    "claim_snippet": "Lemma 3.4 shows sub-Gaussianity implies smoothness of the auxiliary distributions used to construct reference distributions for learning from positive examples alone (Lemma 3.4)."
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  "space_id": "neonforestmist/unknown-truncation-linear-regression-repro",
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