L1 ⚛ L1-529 ⊙ Testnet

Glaucoma Optic-Disc Cupping Classification (PWDR)

Medical Imaging · Optic disc + cup segmentation from fundus with cup-to-disc-ratio glaucoma readout

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⬇ principle.md ⬇ principle.json

Fork L1-529

⬇ L1-529.md ⬇ L1-529.json

Prompt — copy into your LLM

You are helping me submit a MODIFICATION of L1-529 (Glaucoma Optic-Disc Cupping Classification (PWDR)) to the PWM Protocol — a Principle (L1) artifact.

I will paste a Markdown template (or the current L1-529.md).
1. Rewrite the Markdown so the science is correct and clearly explained for my change.
2. Regenerate the sibling L1-529.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

y = ∫_A dA `L.glaucoma_severity_classifier` `L.rnfl_defect_detection` `L.isnt_rule_check` `L.cdr_measurement` `L.disc_cup_segmentation` `L.fundus_acquisition` x + n,    n ~ 𝒩(0, σ²)

world state x (1D glaucoma severity)

→

L · fundus acquisition `L.fundus_acquisition`

→

L · disc cup segmentation `L.disc_cup_segmentation`

→

L · cdr measurement `L.cdr_measurement`

→

L · isnt rule check `L.isnt_rule_check`

→

L · rnfl defect detection `L.rnfl_defect_detection`

→

L · glaucoma severity classifier `L.glaucoma_severity_classifier`

→

Spatial integration ∫_A dA

→

observation y (photon detector)

Noise: additive Gaussian noise

Markdown — human-readable source of truth

⚙ auto-generated

⬇ L1-529.md

# ⚛ L1 Principle — Glaucoma Optic-Disc Cupping Classification (PWDR) **ID:** `L1-529` · **Status:** ⊙ Testnet (genesis catalog) > **🌐 Domain:** Medical Imaging — *Optic disc + cup segmentation from fundus with cup-to-disc-ratio glaucoma readout* > **🎯 Problem class:** linear inverse with categorical readout · **🧮 Solution space:** 1D glaucoma severity > **📡 Carrier:** photon · **🌫 Noise:** gaussian > **⚖ Difficulty (δ):** 3 · **⛓ Block:** 41553360 --- ## 🧠 1. Introduction **Glaucoma Optic-Disc Cupping Classification (PWDR)** is a **linear inverse with categorical readout** whose unknown lives in **1D glaucoma severity** space, within the **Optic disc + cup segmentation from fundus with cup-to-disc-ratio glaucoma readout** sub-domain of **Medical Imaging**. Measurements consist of photons collected by an optical detector via a **fundus with glaucoma grading** sensing mechanism. The forward operator applies, in order: L · fundus acquisition operator; L · disc cup segmentation operator; L · cdr measurement operator; L · isnt rule check operator; L · rnfl defect detection operator; L · glaucoma severity classifier operator; pixel-level spatial averaging on the detector. Observations are corrupted by additive Gaussian noise. Existence inherited from L1-049. Uniqueness conditional on adequate disc visibility (no media opacity). Stability dominated by physiologic_cupping_variant (large physiologic cups can mimic glaucoma) and tilted_disc_anatomy. Joint Hadamard well-posedness established by Bourne 2016 (ICO Glaucoma Guidelines), Spaeth 2002 (Disc Damage Likelihood Scale), Jonas 1989 (foundational neuroretinal rim morphometry), Li 2018 (deep learning glaucoma detection benchmark). ## ⚙ 2. Forward Model Physical chain: **x** → L · fundus acquisition → L · disc cup segmentation → L · cdr measurement → L · isnt rule check → L · rnfl defect detection → L · glaucoma severity classifier → Spatial integration → **y** (detector). ``` y = ∫_A dA `L.glaucoma_severity_classifier` `L.rnfl_defect_detection` `L.isnt_rule_check` `L.cdr_measurement` `L.disc_cup_segmentation` `L.fundus_acquisition` x + n, n ~ 𝒩(0, σ²) ``` **Measurement DAG:** | Primitive | What it does | |---|---| | `L.fundus_acquisition` | L · fundus acquisition operator | | `L.disc_cup_segmentation` | L · disc cup segmentation operator | | `L.cdr_measurement` | L · cdr measurement operator | | `L.isnt_rule_check` | L · isnt rule check operator | | `L.rnfl_defect_detection` | L · rnfl defect detection operator | | `L.glaucoma_severity_classifier` | L · glaucoma severity classifier operator | | `int.spatial` | Pixel-level spatial averaging on the detector | ## 🔬 3. Physics Fingerprint | Property | Value | |---|---| | Domain | Medical Imaging | | Sub domain | Optic disc + cup segmentation from fundus with cup-to-disc-ratio glaucoma readout | | Carrier | photon | | Problem class | linear_inverse_with_categorical_readout | | Solution space | 1D_glaucoma_severity | | Noise model | gaussian | | Integration axis | spatial | | Difficulty delta | 3 | | L dag | 5.6 | ## 📡 4. Measurement Model Existence inherited from L1-049. Uniqueness conditional on adequate disc visibility (no media opacity). Stability dominated by physiologic_cupping_variant (large physiologic cups can mimic glaucoma) and tilted_disc_anatomy. Joint Hadamard well-posedness established by Bourne 2016 (ICO Glaucoma Guidelines), Spaeth 2002 (Disc Damage Likelihood Scale), Jonas 1989 (foundational neuroretinal rim morphometry), Li 2018 (deep learning glaucoma detection benchmark). | Metric | Value | |---|---| | Metric | categorical_accuracy | | Secondary | sensitivity_for_advanced_glaucoma | ## 📏 5. Operating Range (Ω) **Center problem class:** `glaucoma_disc_pwdr` · **Forward operator:** `glaucoma_disc_pwdr_forward` **Center point:** | Parameter | Unit | Value | |---|---|---| | H | px | 2048 | | W | px | 2048 | | Snr db | dB | 30 | | Image quality | — | 0 | | Rgb calibration | — | 0 | | Pallor mimicker | — | 0 | | Pixel resolution um | µm | 5 | | Tilted disc anatomy | — | 0 | | Field of view degrees | — | 30 | | Physiologic cupping variant | — | 0 | | Peripapillary atrophy overlap | — | 0 | | Manual grader inter rater kappa | — | 0 | **Allowed bounds:** | Parameter | Unit | Range | |---|---|---| | H | px | 512 – 4096 | | W | px | 512 – 4096 | ## 🎯 6. Tolerance (ε) **Center tolerance:** 0.85_accuracy | Metric | Range | |---|---| | Categorical accuracy | 0.5 – 0.99 | ## ⚖ 7. Hardness Function Hardness scales as **`epsilon_fn`** on **categorical_accuracy**, with κ = `80` and δ = `3`. ## 💾 8. Reference Dataset - **primary** · weight 1.0 · IPFS _(not pinned yet)_ ## 9. On-chain Registration - **Chain hash:** `0xe7aef74be727afd2ae3572ec25bb1d6fe089484fae36b603285d906a4e4c1305` - **Chain tx hash:** `0x4ae9e22989c9201a9492a07a2434377889e0a6f3a33067f3cc42df72fb8bc3c3` - **Chain block:** `41553360` --- ## File Mapping This bundle consists of: `L1-529.md`, `L1-529.json`. | File | Role | How to regenerate | |------|------|-------------------| | `L1-529.md` | Source of truth — edit this | Human or LLM | | `L1-529.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 `L1-529`._ _Edit it, regenerate the JSON, and submit at [/submit](/submit) to claim the artifact._

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L2-529-001 Glaucoma Optic-Disc Cupping Classification (PWDR) — Spec Skeleton

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📋 JSON metadata

{
  "artifact_id": "L1-529",
  "chain_block": 41553360,
  "chain_hash": "0xe7aef74be727afd2ae3572ec25bb1d6fe089484fae36b603285d906a4e4c1305",
  "chain_tx_hash": "0x4ae9e22989c9201a9492a07a2434377889e0a6f3a33067f3cc42df72fb8bc3c3",
  "domain": "Medical Imaging",
  "hardness_fn": {
    "delta": 3,
    "kappa": 80,
    "metric": "categorical_accuracy",
    "type": "epsilon_fn"
  },
  "initiator_dataset": [
    {
      "ipfs_cid": null,
      "license_hash": null,
      "name": "primary",
      "weight": 1.0
    }
  ],
  "layer": "L1",
  "observable_profile": {
    "metric": "categorical_accuracy",
    "regime": "Existence inherited from L1-049. Uniqueness conditional on adequate disc visibility (no media opacity). Stability dominated by physiologic_cupping_variant (large physiologic cups can mimic glaucoma) and tilted_disc_anatomy. Joint Hadamard well-posedness established by Bourne 2016 (ICO Glaucoma Guidelines), Spaeth 2002 (Disc Damage Likelihood Scale), Jonas 1989 (foundational neuroretinal rim morphometry), Li 2018 (deep learning glaucoma detection benchmark).",
    "secondary": "sensitivity_for_advanced_glaucoma"
  },
  "physics_fingerprint": {
    "L_DAG": 5.6,
    "carrier": "photon",
    "difficulty_delta": 3,
    "domain": "Medical Imaging",
    "integration_axis": "spatial",
    "noise_model": "gaussian",
    "primitives": [
      "L.fundus_acquisition",
      "L.disc_cup_segmentation",
      "L.cdr_measurement",
      "L.isnt_rule_check",
      "L.rnfl_defect_detection",
      "L.glaucoma_severity_classifier",
      "int.spatial"
    ],
    "problem_class": "linear_inverse_with_categorical_readout",
    "sensing_mechanism": "fundus_with_glaucoma_grading",
    "solution_space": "1D_glaucoma_severity",
    "sub_domain": "Optic disc + cup segmentation from fundus with cup-to-disc-ratio glaucoma readout",
    "title": "Glaucoma Optic-Disc Cupping Classification (PWDR)"
  },
  "size_tiers": {
    "allowed_forward_operators": [
      "glaucoma_disc_pwdr_forward",
      "glaucoma_ddls_pwdr_forward",
      "glaucoma_with_visual_field_pwdr_forward"
    ],
    "allowed_omega_dimensions": [
      "H",
      "W",
      "field_of_view_degrees",
      "pixel_resolution_um",
      "RGB_calibration",
      "SNR_dB",
      "image_quality",
      "physiologic_cupping_variant",
      "pallor_mimicker",
      "tilted_disc_anatomy",
      "peripapillary_atrophy_overlap",
      "manual_grader_inter_rater_kappa"
    ],
    "allowed_problem_classes": [
      "glaucoma_disc_pwdr",
      "glaucoma_ddls_pwdr",
      "glaucoma_screening_pwdr"
    ],
    "center_spec": {
      "epsilon_fn_center": "0.85_accuracy",
      "forward_operator": "glaucoma_disc_pwdr_forward",
      "input_format": "disc_centered_fundus_with_glaucoma_label",
      "omega": {
        "H": 2048,
        "RGB_calibration": 0.0,
        "SNR_dB": 30,
        "W": 2048,
        "field_of_view_degrees": 30,
        "image_quality": 0.0,
        "manual_grader_inter_rater_kappa": 0.0,
        "pallor_mimicker": 0.0,
        "peripapillary_atrophy_overlap": 0.0,
        "physiologic_cupping_variant": 0.0,
        "pixel_resolution_um": 5,
        "tilted_disc_anatomy": 0.0
      },
      "problem_class": "glaucoma_disc_pwdr"
    },
    "epsilon_bounds": {
      "categorical_accuracy": [
        0.5,
        0.99
      ]
    },
    "omega_bounds": {
      "H": [
        512,
        4096
      ],
      "W": [
        512,
        4096
      ]
    }
  },
  "staked_pwm": 0.0,
  "status": "testnet",
  "sub_domain": "Optic disc + cup segmentation from fundus with cup-to-disc-ratio glaucoma readout",
  "title": "Glaucoma Optic-Disc Cupping Classification (PWDR)"
}

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