🌐 Instrument Regime Map — Mini‑Schema (Human‑Readable)

📘 Regime Map Legend#

💚 Green Zone — “Stable & Direct”#

• Low drift
• Transparent behavior
• Minimal inference
• Predictable across conditions

💛 Yellow Zone — “Assumption‑Heavy”#

• Model‑dependent
• Mixed‑regime behavior
• Environmental sensitivity
• Compensation & filtering layers

❤️ Red Zone — “Fragile & Inference‑Heavy”#

• Nonlinear or unstable
• Substrate‑sensitive
• Multi‑stage inference
• Drift‑prone or opaque

🧭 SET Axes (Substrate Anchors)#

• 🌀 Spin — polarization, magnetic coupling
• ⚡ Elec — sensor readout, digital logic
• 🔥 Temp — drift, stability, compensation

This schema is intentionally minimal. It mirrors your triadic structure and keeps contributors aligned.

instrument_regime_map:
  name: <string>                # instrument or FW/SW module
  zone: <green|yellow|red>      # triadic classification
  substrate_axes:
    spin: <notes>               # only if relevant
    elec: <notes>
    temp: <notes>
  pos_regime:
    description: <string>       # stable behavior
    conditions:                 # optional
      - <string>
  q_regime:
    description: <string>       # transitional behavior
    conditions:
      - <string>
  neg_regime:
    description: <string>       # fragile behavior
    conditions:
      - <string>
  alignment_notes: <string>     # for green/yellow
  containment_notes: <string>   # for red

This is not meant to be machine‑validated — it’s a conceptual scaffold that keeps every contributor writing in the same shape.

✨ Teaser Examples (Short, Readable, Canon‑Aligned)#

These are intentionally tiny — just enough to show the pattern.

Example 1 — Accelerometer (Green Zone)#

instrument_regime_map:
  name: Accelerometer
  zone: green
  substrate_axes:
    spin: not relevant
    elec: stable sensor readout
    temp: minor drift
  pos_regime:
    description: stable acceleration measurement
    conditions:
      - rigid mounting
      - steady temperature
  q_regime:
    description: mild drift or vibration coupling
  neg_regime:
    description: saturation or nonlinear response
  alignment_notes: stable, direct, low-inference

Example 2 — Automated Peak Fitting (Yellow Zone)#

instrument_regime_map:
  name: Automated Peak Fitting Software
  zone: yellow
  substrate_axes:
    spin: not relevant
    elec: digital computation
    temp: not relevant
  pos_regime:
    description: clean peaks, high SNR
  q_regime:
    description: overlapping peaks, baseline drift
  neg_regime:
    description: unstable fits, model mismatch
  alignment_notes: model assumptions must be explicit

Example 3 — AI‑Based Signal Interpretation (Red Zone)#

instrument_regime_map:
  name: AI-Based Signal Interpretation Tools
  zone: red
  substrate_axes:
    spin: not relevant
    elec: digital computation
    temp: upstream sensor-dependent
  pos_regime:
    description: clean, well-represented data
  q_regime:
    description: domain shift or partial mismatch
  neg_regime:
    description: out-of-distribution inputs, unstable predictions
  containment_notes: dataset boundaries and version drift must be documented

🧭 Why this schema works#

• It’s small — contributors won’t feel intimidated.
• It’s structural — every file ends up shaped the same way.
• It’s triadic — pos/Q/neg is always visible.
• It’s substrate‑aware — SET anchors remain central.
• It’s future‑proof — works for hardware, firmware, software, and hybrids.

🧩 Regime Map Schema (Mini)#

name: instrument/module
zone: 💚 / 💛 / ❤️
substrate_axes: 🌀 ⚡ 🔥
pos_regime: stable behavior
q_regime: transitional behavior
neg_regime: fragile behavior
notes: alignment or containment