{"id":2690,"job_id":5591,"problem_id":1,"lane_id":32,"type":"explore","user_id":1,"model":"deepseek-v4-flash","provider":"deepseek","report_md":"# Report — route 254 first look (job #5591, explore / first_look, lane dir-558, general)\n\n**What was tested.** Route 248 (#2685) identified the sub-Poisson block deficit `1−V(h)` of route 245\nwith the Hardy–Littlewood 4-tuple kernel `r_pred(d)`, but only by matching its **shape**; the dimensional\nnormaliser that would make the match **absolute** was never derived, and the worst cell (8.9% at\n`h=2^20`) was in the direction of extra growth. This first look derives a candidate normaliser and tests\nit on the **recorded** data (no new sieve; no published computation reproduced).\n\n**The normaliser (derived, then tested).** Writing route 247's wheel-matched null as admissible openers\n(density `ρ_W=0.04363323…`) with intensity-matched site probability `p=(2C2/(ln x)²)/ρ_W` so\n`Σp=μ(b)`, the block variance decomposes as `1−V(h)=Σp²/μ − Σ_d2(h−|d|)(P(d)−E0(d))/(X−|d|)/μ`; the\ncovariance integral with `Σ_d(h−|d|)r_pred(d)=−hF(h)` and `Σp²/μ≈p` gives\n\n    N(x) = 4C2/(ρ_W (ln x)²)  ⟹  pred(h,x) = N(x)·F(h),   F(h)=(1/h)Σ_{d<h}(h−|d|)(−r_pred(d)).\n\nThe single change vs the naive `4C2/(ln x)²` is the `1/ρ_W`; it moves the prediction from **23× off** to\nwithin 25% (median ~4%) of route 245's measured `1−V`.\n\n**Result.** `compute_hk.py` + `check_hk.py` over the 15 recorded cells (`x∈{2^27,2^28,2^30,2^32}`,\n`h∈{2^14,2^16,2^18,2^20}`):\n\n- **Test A (absolute closure).** 13/15 cells within the pre-registered ±15%; failures are `x=2^28`,\n  `h=2^16` (+16.2%) and `h=2^18` (+25.2%). → **A-CLOSED fails, A-SCALE holds** (all `|dev|≤0.35`, all\n  predictions positive). The residual is **not monotone in `h`** and is concentrated at `x=2^28` — an\n  `h`-structure, not a simple large-`h` tail.\n- **Test B (where the deficit lives).** At `X=2^27` the recorded 22-lag ladder supplies only\n  `R_corr = 0.225, 0.225, 0.173` of the block covariance for `h=2^14,2^16,2^18`. So the sampled short\n  lags carry ~17–23% of the deficit; the rest lies beyond the recorded ladder — which is exactly why the\n  **cumulative** `F(h)` (all `d≡0 mod 6`) is the right instrument, and why a 22-lag reading cannot\n  transfer to the aggregate.\n\n**Checker.** `check_hk.py` re-derives `S4(d)` by the **direct** product over primes ≤2^20 (anchors\n`r_pred(6)=−0.05803`, `r_pred(3840)=+0.02444`), certifies the factorization identity on a sample, and\nrecomputes both tests and the decisions: **37/0, exit 0**; `--corrupt` (wrong `p=2` density factor)\n**21 FAIL, exit 1**. `Gate A` reproduced from #2685. Sources hash-verified (`twin_two_point.json`\nsha `27f4d53b…`; `compute_gz.json` of #2673).\n\n**Rung / scope.** The normaliser formula, the two tests and the decisions are **measured** (deterministic\nrecomputation from recorded blobs). Conditional on #1933/#1929, on #2678's HL identification, and on\n`rel(d)≈r_pred(d)`. One realization, nested windows (`2^27⊂2^28⊂2^30⊂2^32`); Test B uses only the 22\nrecorded lags. No asymptotic claim; **no bound on `G2`, `π2` or the twin-prime conjecture**. HL remains\na conjecture. `PREREGISTRATION_hk.md` is frozen before the checker but **not** before the first\nexploratory number (disclosed there): the experiment is deterministic, so no target could be tuned.\n\n**Outcome: `promising`.** The route's step (a) is essentially tractable — the normaliser is\n`4C2/(ρ_W(ln x)²)` and it is right to ~4% (median) — but it does **not** reach the pre-registered ±15%\nat every cell, and Test B shows the aggregate needs the full kernel. This justifies exactly one bounded\nnext experiment (route 254's step (b), refined): re-block route 245's recorded sieve to `h=2^22,2^24`,\nintegrate the full `d≡0 mod 6` kernel, and use the estimator's own `μ(b)` in place of `(ln x)²`.\n`next_step.json` / `recipe_hk.md` give the procedure and the pre-registerable bands. The route returns\nit builds on are cited (`depends_on` = [2685, 2678, 2673, 2625]).\n\n**Disclosure.** `49` of @Benjaminsen's returns wait for a verdict (one line, per the brief). No\n`request_review` (this is an explore/first look; recorded without review unless a structured result\nrequests validation). No channel \"claim\" message: there is no tested local subcommand for it, so the\nreturn itself is the completion note (recorded as an omission). `next_step.required_sources` left empty.\n","patch":null,"cpu_hours":0.05,"hashes":{"sah.py":"21a1d3556191bf54458b13fa0ebe41b4550fb92a33ab9bee6518d82ef222c843","recipe.md":"58d13ba9dbc77ee626b2942f8e24c645c5c27b9af9c097c2731e549bb109d031","report.md":"4b71ced1ecdeb22e1b5950501790d1d1e0cec9e51242ce7cf58e2ffd125c88ac","check_hk.py":"ab0b7f1945e7e2a7d0a59201f089ecca257df99828065881cf9d709e65605585","evidence.md":"1065a669da41300bdb8d94b066c4e1952aa110185199b9f0e699f181fb5feea8","fetch_hk.py":"6578fbe9c70c752601feb97ff045d61c4d70f27090619d0ef27119f809a39651","check_hk.out":"12e086403e458dbd447a9afa7975d5ddb022e555c4dd3c76877394ee59a1fb7c","prior-art.md":"c3a6a7e3a991923a13238da84791ad8ae57d3e7b0659a16351f8a20e80c04add","compute_hk.py":"39fd190f4afe15df935b6e962db6724f3499d5dda78ad7e8c64a316a86be84f8","compute_hk.out":"3d9d1e7a6b7fceef097d439441676123dbba5dc9a81473d67c69c0a52323aa67","next-step.json":"f320ab83a0865ac4debd33bec558cabfbd902288cc6cd1a609dd001221d830f6","route-254.json":"e69089dab1e1325e4d359da2fac0f1859b68a296bd40ea779649bfd807862bdf","results_hk.json":"bf228cbdd804de66808f6389136f36c2dc3d9fd98d359b7aef51d3e8c2040d5d","return-2637.json":"8171b4dfb2ab90182b84e1ae9dc920dae0117a8c8d0605755c889f0a66e1f460","return-2673.json":"d7088e72d087246dd234415b30311871f426defba36beddec099b1839581a500","return-2685.json":"4d577ff876d756164d9548ead967399de7ffa277a9fe85b1cd5f57f57d67dd94","fetch_files_hk.py":"7f5b78911ec4009f65e28366482869bdc14762981e38d0eadf76c29d13cca891","PREREGISTRATION.md":"bdecdc117e91e30ce7d8bb65f5db0ff6748b0df6a753fcec153f419be24c263f","check_hk.control.out":"c05b2a35af8ac1f5b1989ddc05932abf426b1c01d2f60c89af79584e8e2e7137","export_transcript.py":"029efc05e4b791b297f3cb254a24887e3d23b98b1ab4a6639d1f6dc7b69cc82f","served-twin-two-point.json":"27f4d53b32e44e6942f0b0904b52c66996985b6d5a78265f84841ad23f06b425","served-compute-gz-2673.json":"58218ca0bb76b403cab16768a3fa2323626d4b2b568a95b18cafe7a49236d1f1","note-route254-normaliser-firstlook-5591.md":"3cb1d1181877950c9bfb51abe67f8560f3448d98e0032203091378439d5b489f"},"author_rung":null,"status":"recorded","final_rung":"recorded","created_at":"2026-10-10T09:04:56.284Z","repo_url":null,"commit":null,"cites":{"returns":[2685,2678,2673,2625,2631,2637]},"tokens":{"log":"custom","input":0,"models":{"deepseek-v4-flash":0},"output":0,"source":"none","entries":0,"cache_read":0,"cache_write":0,"observed_models":["deepseek-v4-flash"]},"paper_slug":null,"revision_path":null,"revision_sha":null,"recipe_md":"# Recipe — route 254 first look (job #5591)\n\nTools: `python3` (stdlib only). No compiled code, no new sieve, no network beyond the journaled\nfetches. Runs in seconds.\n\n## Fetch the recorded sources (journaled, hash-verified)\n```\npython3 fetch_hk.py          # route 254, returns 2685/2678/2673/2625/2637/2631, research-protocol, board\npython3 fetch_files_hk.py    # served/twin_two_point.json (sha 27f4d53b…) — sha_match=True\n# served/compute_gz_2673.json fetched from #2673's files list (sha d361c4f2…, sha_match=True)\n```\nBlobs land under `served/` and are re-hashed on write; `sha_match=True` is printed.\n\n## Run the experiment\n```\npython3 compute_hk.py > compute_hk.out      # Test A normaliser table + Test B covariance integral\npython3 check_hk.py > check_hk.out          # independent: 37 checks, 0 FAIL, exit 0\npython3 check_hk.py --corrupt > check_hk.control.out   # 21 FAIL, exit 1 (wrong p=2 factor)\n```\n\n## Objects\n`r_pred(d)=S4(d)ρ_W²/((2C2)²ρ2(d))−1` (#2685), `d≡0 mod 6`;\n`ρ_W = 0.5∏_{p∈{3,5,7,11,13,17}}(p−2)/p = 0.04363323…`; `F(h)=(1/h)Σ_{d<h}(h−d)(−r_pred(d))`;\ncandidate normaliser `N(x)=4C2/(ρ_W (ln x)²)`; prediction `1−V(h)=N(x)F(h)`.\nFast `S4`: only primes dividing `d(d±2)` change `ν_p` from 4, so\n`S4 = G·(−1/2)·(−1)·∏_{p≥5,p|d}(1−2/p)/(1−4/p)·∏_{p≥5,p|d±2}(1−3/p)/(1−4/p)`,\n`G=∏_p(1−4/p)(1−1/p)^{−4}`. The checker re-verifies this identity against the direct product.\n\n## Traps\n- The kernel is defined only for `d ≡ 0 mod 6`: any other `d` gives `ν_3=3` ⇒ `ρ2=0` ⇒ division by\n  zero. Sample/iterate only `d≡0 mod 6`.\n- The checker's full `F` grid needs the factorization path; a *direct* prime product over 2^20 for\n  every `d` is intractable (~1.7·10^5 × 8·10^4). Direct is used only for the anchors + an 18-value\n  sample to certify the identity.\n- `served/compute_gm.py` / `compute-twin-pair-two-point.py` are served *sanitised* (paths replaced), so\n  their sha does not match the record; the *data* blob `twin_two_point.json` does match.\n- Keep the transcript raw/scrubbed scratch out of the tree; scrub before publishing.","verification":null,"target":null,"finding":null,"human_md":null,"provisional":false,"effects_applied_at":null,"effort":null,"also_fix":null,"transcript_omitted":{"share":0,"omitted":0,"outputs":0},"patch_hash":null,"superseded_by":null,"duplicate_of":null,"transcript_resubmitted_at":null,"file_notes":null,"research":{"outcome":"promising","route_id":254,"next_step":{"method":"Two bounded parts on recorded data, no new mathematical object. (i) Replace the leading normaliser's (ln x)^-2 by the ESTIMATOR'S OWN exact block mean, i.e. test pred(h,x)=4C2*(sum_{n in b} ln^{-2} n)/rho_W * F(h) / (sum over the block) using the per-block mu(b) already recorded in #2673; this removes the (ln x) approximation that Test A flagged. (ii) Re-block route 245's recorded segmented sieve (compute_gz.py, return #2673) to h in {2^22,2^24} at x=2^30 and x=2^32, and integrate the FULL kernel F(h) over all d=0 mod 6 to 2^24 (not a 22-lag subset -- job #5591 Test B showed the 22-lag ladder carries only ~20% of the covariance). Pre-register the +-15% band (and a +-25% rescue band) before the re-block.","compute":{"ram_gb":2,"disk_gb":1,"cpu_hours":0},"failure":"any cell outside +-25% -> a precisely scoped h/x structure in the normaliser; record it, keep the HL aggregate closure at its confirmed scope, and hand the departure to route 245 for a changed-mechanism attempt.","success":"every cell (the 15 of #5591 plus the new 4) lies within +-15% -> the aggregate closure holds absolutely at larger h; report the absolute law and the confirmed route-87 yardstick correction, and the route rests.","question":"Does the derived absolute normaliser N(x)=4C2/(rho_W (ln x)^2) close route 245's aggregate deficit 1-V(h) to the pre-registered +-15% at the ROUTE's larger-h cells (h=2^22,2^24) as well as at h<=2^20 -- or is the +16/+25% x=2^28 residual (job #5591) the first sign of a real h/x structure?","budget_hours":0.5,"required_tools":[],"required_sources":[]},"depends_on":[2685,2678,2673,2625],"evidence_md":"# Evidence — route 254 first look (job #5591)\n\n**What the evidence changes.** Route 248's identification (\"the sub-Poisson block deficit is the\nHardy–Littlewood local factor\") is a **shape** match at one scale; route 254 (proposed by #2685) asks\nwhether the *same* kernel gives an **absolute** prediction of route 245's aggregate deficit `1−V(h)`,\nand whether it holds past `h=2^20`. This first look makes the normaliser explicit and tests it on the\n**recorded** data; it does not reproduce any published computation and runs no new sieve.\n\n**The candidate normaliser (derived, then tested).** Write route 247's wheel-matched null as the\nadmissible openers (density `ρ_W = 0.5·∏_{p∈{3,5,7,11,13,17}}(p−2)/p = 0.04363323…`) each kept with\nintensity-matched site probability `p = (2C2/(ln x)²)/ρ_W`, so `Σ_{n∈b} p(n) = μ(b)`. Then\n`Var(N(b)) = Σp(1−p) + Σ_edges Cov` and, with `rel(d)=P(d)/E0(d)−1 ≈ r_pred(d)`,\n`1−V(h) = Σp²/μ − Σ_d 2(h−|d|)(P(d)−E0(d))/(X−|d|)/μ`. Using `Σp²/μ ≈ p` and `Σ_d(h−|d|)r_pred(d)=−h·F(h)`,\nthe leading term gives the closed normaliser\n\n    N(x) = 4C2 / (ρ_W (ln x)²),     pred(h,x) = N(x)·F(h),   F(h) = (1/h)Σ_{d<h}(h−|d|)(−r_pred(d)).\n\n`N(x)` is exactly `2p`; the extra `1/ρ_W` (vs the naive `4C2/(ln x)²`) is the *only* change that turns\n#2685's shape test absolute.\n\n**Test A — absolute closure (all 15 recorded cells).** `dev = pred/meas − 1`:\n\n| x | h=2^14 | h=2^16 | h=2^18 | h=2^20 |\n|---|---|---|---|---|\n| 2^27 | −4.2% | +12.2% | +10.7% | — |\n| 2^28 | +1.6% | **+16.2%** | **+25.2%** | +1.3% |\n| 2^30 | −0.5% | +5.9% | +2.6% | −9.1% |\n| 2^32 | +2.7% | +3.1% | +4.6% | −1.9% |\n\n13 of 15 cells are inside the pre-registered ±15%; the two failures are `x=2^28` at `h=2^16,2^18`\n(+16.2%, +25.2%). So **A-CLOSED fails, A-SCALE holds** (all `|dev| ≤ 0.35`, all predictions positive).\nFor scale: the naive normaliser `4C2/(ln x)²` (no wheel factor) is off by **~23×** at every cell; the\nderived one is within 25%, median ~4%. The residual is *not* monotone in `h` and is concentrated at\n`x=2^28` — an unexplained `h`-structure, not a simple large-`h` tail.\n\n**Test B — where the deficit lives (X = 2^27, recorded 22-lag ladder only).** The block covariance the\nladder must explain is `Σp² − (1−V)μ`; the 22 measured lags supply\n`R_corr = Σ_d 2(h−|d|)(P(d)−E0(d))/(X−|d|) / [Σp²−(1−V)μ] = 0.225, 0.225, 0.173` for\n`h = 2^14,2^16,2^18`. So the sampled short lags carry only **~17–23%** of the deficit; the rest lies at\nlags beyond the recorded ladder (`d ≤ 15360`) — consistent with a slowly-decaying `d≡0 mod 6` kernel,\nand the reason the **cumulative** `F(h)` (all lags) rather than a 22-lag fit is the right instrument.\n\n**Reproduction.** `compute_hk.py` reads the two served blobs (sha256-verified) and prints the table;\n`check_hk.py` re-derives `S4(d)` by the **direct** product over primes ≤ 2^20 (anchors `r_pred(6)=−0.05803`,\n`r_pred(3840)=+0.02444`), verifies the factorization identity on a sample, recomputes `F`, both tests\nand the decisions: **37 checks, 0 FAIL, exit 0**; `check_hk.py --corrupt` (wrong `p=2` density factor)\n**21 FAIL, exit 1**.\n\n**Scope.** Recorded-data recomputation; only `d≡0 mod 6`; `r_pred` is #2685's frozen object. Conditional\non #1933/#1929 and on HL being the right local factor (#2678). `V` is one realization, nested windows.\nNo asymptotic claim; no bound on `G2`, `π2` or the twin-prime conjecture.\n\n**Sources.** `served/twin_two_point.json` (#2637, sha `27f4d53b…`), `served/compute_gz_2673.json`\n(#2673), return #2685 (basis, `F`), route 254 (brief). All fetched read-only and journaled.","prior_art_md":"# Prior art — route 254 first look (job #5591), search 2026-10-10\n\n**Queries run (Serper web search, 2026-10-10):**\n1. \"Hardy-Littlewood singular series pair correlation variance twin primes short intervals sub-Poisson Markov\";\n2. \"variance of pair count Hardy-Littlewood k-tuple singular series block integral normalisation Gorodetsky short intervals\".\n\n**Closest sources inspected.**\n- Keating, Rudnick et al. — \"The Variance of the Number of Prime Polynomials in Short Intervals\"\n  (math.tau.ac.il/~rudnick; IMRN) and Keating, *et al.*, \"Pair correlation and twin primes revisited\",\n  *Proc. R. Soc. A* 472 (2016) 20160548 (arXiv:1604.06124): the **pair-correlation conjecture is\n  equivalent to an asymptotic formula for the variance of a short-interval prime count**. This is the\n  classical object *behind* route 245's statistic; it fixes the **direction** but states the variance of\n  the *prime* count, not of the twin-pair count against route 245's exact discrete HL mean.\n- Goldston–Montgomery (1973), Montgomery–Soundararajan (2004): primes in short intervals fluctuate\n  **less** than the Cramér/Poisson model — the classical origin of the sub-naive direction.\n- Gorodetsky, *Math. Z.* 308 (2024), arXiv:2111.00853: one-class variance limit; **abstract only**\n  (full text bot-blocked). Supplies the asymptotic sub-naive mechanism, not a finite block normaliser.\n- Pintz, \"On the singular series in the prime k-tuple conjecture\" (arXiv:1004.1084): averages of the\n  singular series (Gallagher) — relevant to `Σ_d r_pred(d)`, no block-variance normaliser stated.\n- K. Kedlaya, MIT 18.785 notes \"The Hardy–Littlewood k-tuples conjecture\"; Wolfram MathWorld\n  \"k-Tuple Conjecture\": the singular series `S4(d)` for `{0,2,d,d+2}` (the object `r_pred` uses).\n- The project's own record: route **245** (#2625, #2673), route **247** (#2631, #2637), route **248**\n  (#2678), route **254** origin (#2685). Read at their served shas; no re-derivation.\n\n**Existing attempts and their coverage.** Route 245 measured `V(h)` on an `(x,h)` ladder to `2^32`.\nRoute 247 built the wheel-matched null and measured the lag-resolved ladder at `X=2^27` (22 lags).\nRoute 248 showed `rel(d) ≈ r_pred(d)` at every measured lag (χ²/dof = 0.686). **None** derives the\n**dimensional normaliser** linking the wheel-restricted ratio `r_pred(d)` to `Var(N)/μ`, and none tests\nthe aggregate in **absolute** terms.\n\n**Exact uncovered step.** Derive the normaliser and test `1−V(h) = N(x)·F(h)` absolutely (this first\nlook: candidate `N(x)=4C2/(ρ_W(ln x)²)`, good to 25% but not 15%, and Test B shows the deficit is spread\nbeyond the 22 sampled lags). No external source states this normaliser.\n\n**Access gaps.** Keating *et al.* full text (abstract only); Gorodetsky full text (abstract only). A\nno-match result is **not** a novelty claim: the pair-correlation↔variance direction is classical and\nthis route claims no new mechanism — only a bounded aggregate normaliser test. MathSciNet/zbMATH were\nnot searched (no new literature claim beyond the citations above)."},"research_route_id":254,"verification_plan":null,"verification_fingerprint":null,"review_admitted_at":null,"department_id":"dept_0e793a31e299699dfaaa6fee","run_id":"run_57668eb4295e64984cb90643","triage_lead":null,"revision_base_sha":null,"integration":null,"resolves":null,"paper_exposition":null,"handle":"Benjaminsen","job_brief":"Search online for existing attempts, results, tables and datasets before testing feasibility. Reuse the recorded search and inspect the closest sources and weakest assumption. Use published numbers with citations; do not reproduce them in a first look. Seek the smallest experiment on the uncovered step. Recommend promising only with specific evidence and a bounded next step; do not claim the route is proved. Map the assumptions of any borrowed method onto this problem.\n\nRead GET <project base>/research-routes/254 and return #2685. Return the ordinary report and transcript plus research: {route_id: 254, outcome: \"promising|progress|blocked|inconclusive|known|result\", evidence_md: \"what the evidence changes, <=4000 chars\", prior_art_md: \"updated online search record, sources and exact remaining gap, <=4000\", next_step: {question, method, success, failure, budget_hours} <only for continued pursuit; what to do, never when or how fast; it must not ask for what a return on this route or a linked route already did, and the route returns it builds on go in depends_on or cites.returns>, obstacle: {kind, statement, assumptions, evidence, revisit_when} <for blocked/inconclusive>, depends_on: [<return ids actually required>]}. A result with a distinct next_step requests review and continues pursuit concurrently; omit next_step when no further experiment is warranted. Use known with prior_art_md and no next_step or obstacle when cited prior work already covers the proposed contribution; it stops automatic investigation without requesting review. The evidence grade is separate. Do not close a broad route because one proof attempt failed.","review_deferred":false,"in_triage":false,"triage":[],"lean_statement_binding":null,"lean_execution_binding":null,"lean_scientific_identity":null,"lean_execution_identity":null,"verification_runs":[],"verification_state":null,"verification_summary":null,"canonical_return":null,"review_history":[],"dependencies":[{"id":"2625","status":"recorded","final_rung":"recorded","canonical_return_id":null},{"id":"2673","status":"recorded","final_rung":"recorded","canonical_return_id":null},{"id":"2678","status":"recorded","final_rung":"recorded","canonical_return_id":null},{"id":"2685","status":"recorded","final_rung":"recorded","canonical_return_id":null}],"cited_by":[],"route_dependents":[254],"research_url":"/projects/twin-primes/research-routes/254","transcript_url":"/projects/twin-primes/return/2690/transcript","files":[{"sha256":"4b71ced1ecdeb22e1b5950501790d1d1e0cec9e51242ce7cf58e2ffd125c88ac","name":"report.md","bytes":4341},{"sha256":"1065a669da41300bdb8d94b066c4e1952aa110185199b9f0e699f181fb5feea8","name":"evidence.md","bytes":3690},{"sha256":"c3a6a7e3a991923a13238da84791ad8ae57d3e7b0659a16351f8a20e80c04add","name":"prior-art.md","bytes":3074},{"sha256":"58d13ba9dbc77ee626b2942f8e24c645c5c27b9af9c097c2731e549bb109d031","name":"recipe.md","bytes":2137},{"sha256":"f320ab83a0865ac4debd33bec558cabfbd902288cc6cd1a609dd001221d830f6","name":"next-step.json","bytes":1568},{"sha256":"bdecdc117e91e30ce7d8bb65f5db0ff6748b0df6a753fcec153f419be24c263f","name":"PREREGISTRATION.md","bytes":3848},{"sha256":"39fd190f4afe15df935b6e962db6724f3499d5dda78ad7e8c64a316a86be84f8","name":"compute_hk.py","bytes":4652},{"sha256":"3d9d1e7a6b7fceef097d439441676123dbba5dc9a81473d67c69c0a52323aa67","name":"compute_hk.out","bytes":1258},{"sha256":"ab0b7f1945e7e2a7d0a59201f089ecca257df99828065881cf9d709e65605585","name":"check_hk.py","bytes":5782},{"sha256":"12e086403e458dbd447a9afa7975d5ddb022e555c4dd3c76877394ee59a1fb7c","name":"check_hk.out","bytes":1782},{"sha256":"c05b2a35af8ac1f5b1989ddc05932abf426b1c01d2f60c89af79584e8e2e7137","name":"check_hk.control.out","bytes":3020},{"sha256":"bf228cbdd804de66808f6389136f36c2dc3d9fd98d359b7aef51d3e8c2040d5d","name":"results_hk.json","bytes":3293},{"sha256":"6578fbe9c70c752601feb97ff045d61c4d70f27090619d0ef27119f809a39651","name":"fetch_hk.py","bytes":1158},{"sha256":"7f5b78911ec4009f65e28366482869bdc14762981e38d0eadf76c29d13cca891","name":"fetch_files_hk.py","bytes":1338},{"sha256":"27f4d53b32e44e6942f0b0904b52c66996985b6d5a78265f84841ad23f06b425","name":"compute-twin-pair-two-point.json","bytes":3966},{"sha256":"58218ca0bb76b403cab16768a3fa2323626d4b2b568a95b18cafe7a49236d1f1","name":"compute_gz.json","bytes":4858},{"sha256":"8171b4dfb2ab90182b84e1ae9dc920dae0117a8c8d0605755c889f0a66e1f460","name":"return-2637.json","bytes":26235},{"sha256":"d7088e72d087246dd234415b30311871f426defba36beddec099b1839581a500","name":"return-2673.json","bytes":30094},{"sha256":"e69089dab1e1325e4d359da2fac0f1859b68a296bd40ea779649bfd807862bdf","name":"route-254.json","bytes":23262},{"sha256":"4d577ff876d756164d9548ead967399de7ffa277a9fe85b1cd5f57f57d67dd94","name":"return-2685.json","bytes":27136},{"sha256":"3cb1d1181877950c9bfb51abe67f8560f3448d98e0032203091378439d5b489f","name":"note-route254-normaliser-firstlook-5591.md","bytes":2770},{"sha256":"21a1d3556191bf54458b13fa0ebe41b4550fb92a33ab9bee6518d82ef222c843","name":"sah.py","bytes":56280},{"sha256":"029efc05e4b791b297f3cb254a24887e3d23b98b1ab4a6639d1f6dc7b69cc82f","name":"export_transcript.py","bytes":10230},{"sha256":"cc32fc0e140b94128a66053407c00547baadb81d7b8dad80aecf7d6e409b2761","name":"served-compute_gm.py","bytes":6067}],"decided_by_author_handle":false,"reviews":[],"decisions":[],"decision":null,"duplicates":[],"cited_messages":[]}