The Blind Machine

Independently review The Blind Machine paper the way a careful, skeptical referee would — verifying every claim against evidence rather than accepting it.

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Install the whole repository into your agent's skills directory in one command — it unpacks as a ready-to-use review/ folder (change -C to your skills path):

curl -fsSL https://blindmachine.org/skills/review/archive | tar xz -C ~/.claude/skills

Or fetch just the recipe to read or execute inline:

curl https://blindmachine.org/skills/review.md
review / references / review-dimensions.md

65 lines · 2.94 KB · sha256:2e4602f57e30…4f312ea2

# Review dimensionsWork through all six. For each finding, record severity, location, the problem, theevidence, and a concrete fix.## 1. Claim-evidence integrityTrace every headline number to its source and confirm it matches (see`claim-evidence-map.md`). Specifically:- The synthetic exactness taxonomy: six applications, `max_error` 0, 128-bit  ciphertext sizes 262,282 / 1,310,882 / 2,621,791 bytes, 5× and 10× premiums.- The real-genome studies (Section 11): E5 mean absolute AF delta ≈ 0.0609; E6 max  F_ST-like 0.1363 and 624 suppressed rows; E7 recovery rates (1.000 under  min-N-20, 0.000 under freeze, 0.125 under query budget 5); E8 exact product  moments and max `r2` 1.0000.Flag any value that does not match, any transposed digit, and any table whose rowsdisagree with its cited CSV/JSON.## 2. Security analysis (Section 9)- Confirm the coverage matrix (Table 4) and the per-attack catalog agree: every  threat in the matrix has a structured subsection, and every subsection maps to a  matrix row.- Confirm every attack subsection uses the same seven-field template (Adversary,  Attack, Assets at risk, Platform control, Verification hook, Status, Residual  risk / evidence) and that each Status is drawn from the fixed vocabulary  (Prevented / Detectable / Mitigated / Residual / Out of scope), consistently with  the matrix.## 3. Honesty and overclaiming- The real-genome studies must be framed as aggregate-only workflow demonstrations  on public reference data — NOT biomedical validation or population-genetics  estimates.- The F_ST-like and LD `r2` values must be labeled simplified small-panel contrasts;  the E8 `r2` = 1.0000 pair must be flagged as a small-count artifact; the  below-quorum E8 caveat (25 samples < floor of 30) must be present.- The certificate honesty box must state that the certificate binds artifacts and  policy facts and does NOT by itself prove correct computation, correct decryption,  contributor identity, or bounded output-privacy leakage.- Flag any sentence that claims more than the evidence supports.## 4. Citation and cross-reference integrity- Every reference R1-R37 is both defined and cited, with no gaps or orphans.- Every "Section N", "Table N", and "Figure N" reference resolves to the right  target; tables are numbered 1-16 and figures 1-8; the Appendix A index matches the  body.## 5. Reproducibility- The paper gives a concrete, runnable reproduction path (Appendix B); the commands  exist; the open CLI, open applications, and public data are sufficient to  reproduce every result without the hosted service. Optionally run the `replicate`  skill and confirm the numbers.## 6. Scope and framing- The contribution claims (Section 2) are supported and appropriately bounded.- The threat model's assumptions are stated.- The limitations are acknowledged: single keyholder, metadata leakage,  output-privacy as the largest residual risk, and synthetic-plus-small-real  evidence.

Part of the Independently review The Blind Machine paper agent skill.

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