L2 📐 L2-410-001 ⊙ Testnet

Tumor Growth Model Inversion — Nominal + Mismatch Specs

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Layer template

⬇ spec.md ⬇ spec.json

Fork L2-410-001

⬇ L2-410-001.md ⬇ L2-410-001.json

Prompt — copy into your LLM

You are helping me submit a MODIFICATION of L2-410-001 (Tumor Growth Model Inversion — Nominal + Mismatch Specs) to the PWM Protocol — a Digital Twin (L2) artifact.

I will paste a Markdown template (or the current L2-410-001.md).
1. Rewrite the Markdown so the science is correct and clearly explained for my change.
2. Regenerate the sibling L2-410-001.json so EVERY field matches the Markdown.
3. Keep the schema in the "File Mapping" footer at the bottom of the MD.
4. Keep the parent reference unchanged unless I ask otherwise.
Rules: the Markdown is the source of truth; use SI units; do NOT invent benchmark scores.
Output each file in its own fenced code block tagged with the filename.

Here is my template:
[PASTE THE .md HERE]

⚙ Forward Model

derived from principle L1-410

y = `S.bootstrap.uncertainty_tumor` `O.nls.tumor_fit` ∂_t x

world state x (tumor growth parameter vector)

→

Time derivative ∂_t

→

O · nls · tumor fit `O.nls.tumor_fit`

→

S · bootstrap · uncertainty tumor `S.bootstrap.uncertainty_tumor`

→

observation y (N/A detector)

Noise: log-normal multiplicative noise

Markdown — human-readable source of truth

⚙ auto-generated

⬇ L2-410-001.md

# 📐 L2 Digital Twin — Tumor Growth Model Inversion — Nominal + Mismatch Specs **ID:** `L2-410-001` · **Status:** ⊙ Testnet (genesis catalog) **Parents:** ⬆ Principle [`L1-410`](/artifact/l1/L1-410) > **🎯 Tolerance (ε):** expression > **⚖ Difficulty score:** 0.25 · **Delta tier:** 5 > **⛓ On-chain block:** 41555222 --- ## 1. Domain Ω **Type:** `range` | Parameter | Unit | Range | |---|---|---| | Tumor volume mm3 | — | 10 – 100000 | | N imaging timepoints | — | 3 – 50 | | Imaging noise percent | — | 2 – 50 | | Growth rate lambda day | — | 0.001 – 0.5 | ## 2. Tolerance (ε) **Type:** `fn` ``` 10 + 5 * (imaging_noise_percent / 10) ** 0.5 ``` ## 3. Difficulty | Property | Value | |---|---| | Difficulty score | 0.25 | | Delta tier | 5 | ## 4. Fingerprint `840f8eb3224f74c538aab83bea3539f35c221493f913e293d2a29d38b2f1ea9b` ## 5. On-chain Registration - **Chain hash:** `0xb391919df97c7668bd5e90d538b83011ca392faceb890f614ee4f5565b0fbdc2` - **Chain tx hash:** `0x8473a5ca5c81322e584ead0afe8f602aacca5a447b05cbbe79da42585520b9c6` - **Chain block:** `41555222` --- ## File Mapping This bundle consists of: `L2-410-001.md`, `L2-410-001.json`. | File | Role | How to regenerate | |------|------|-------------------| | `L2-410-001.md` | Source of truth — edit this | Human or LLM | | `L2-410-001.json` | Structured metadata for the registry | LLM regenerates from the sections above | **Prompt for your LLM after editing this Markdown:** > Read the attached Markdown. Regenerate the sibling `.json` so every field matches. > Preserve the schema documented in the rows above. > Output each file in its own fenced code block tagged with the filename. > Output only the JSON object. _This Markdown was auto-synthesized from the catalog row for `L2-410-001`._ _Edit it, regenerate the JSON, and submit at [/submit](/submit) to claim the artifact._

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⌥ Hierarchy

Upstream lineage and downstream children

↑ Upstream

L1 L1-410 Tumor Growth Model Inversion

↓ L3 Benchmark 1 child ▾

L3-410-001-001-T1 T1_nominal

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📋 JSON metadata

{
  "artifact_id": "L2-410-001",
  "chain_block": 41555222,
  "chain_hash": "0xb391919df97c7668bd5e90d538b83011ca392faceb890f614ee4f5565b0fbdc2",
  "chain_tx_hash": "0x8473a5ca5c81322e584ead0afe8f602aacca5a447b05cbbe79da42585520b9c6",
  "delta_tier": 5,
  "difficulty_score": 0.25,
  "epsilon": {
    "expression": "10 + 5 * (imaging_noise_percent / 10) ** 0.5",
    "type": "fn"
  },
  "fingerprint": "840f8eb3224f74c538aab83bea3539f35c221493f913e293d2a29d38b2f1ea9b",
  "layer": "L2",
  "omega": {
    "dims": {
      "N_imaging_timepoints": [
        3,
        50
      ],
      "growth_rate_lambda_day": [
        0.001,
        0.5
      ],
      "imaging_noise_percent": [
        2,
        50
      ],
      "tumor_volume_mm3": [
        10,
        100000
      ]
    },
    "type": "range"
  },
  "parent_l1": "L1-410",
  "status": "testnet",
  "submitted_by": "mainnet_mirror",
  "title": "Tumor Growth Model Inversion \u2014 Nominal + Mismatch Specs"
}

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