# QAG Virology Lab — Presentation Walkthrough

*A slide-style script for presenting the theory. Each section is one "slide".*
*Companion deck: slide deck linked in `docs/DRIVE_ASSETS.md`. Live entry point: `index.html`.*

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## Slide 1 — Title

**QAG Virology Lab**
*Quantum Affinity Gravity meets virology: computing resonant frequencies from viral structure.*
Rodney Alan Ripley Jr.

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## Slide 2 — The question

Every virus is a physical structure — a protein assembly with a measurable mass, atom count, and geometry. If structure determines how a virus resonates, can we compute the frequency at which that resonance becomes disruptive — while leaving host biology untouched?

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## Slide 3 — The framework: QAG

Quantum Affinity Gravity (QAG) is the author's unified-field framework. Its core claim: affinity — the tendency of structures to couple — follows scaling laws anchored to the hydrogen line (1420.405 MHz) and base-12 symmetry (Φ = 1.194797). The virology lab is QAG applied at the micro scale: viral acoustics.

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## Slide 4 — The AVI law: biology meets cosmology

The stub this repo started from named it: *biology and cosmology integration through the AVI law*. The same scaling constants that describe cosmological resonance (hydrogen baseline, base-12 symmetry) are applied to protein assemblies. One math, two scales.

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## Slide 5 — The governing equations

For a target protein assembly (MW_kDa, atom count A_c):

1. **Density proxy:** ρ = MW_kDa / A_c
2. **Affinitic impedance:** Z_v = (MW_kDa × ρ) / K_ASB
3. **Disruptive frequency:** f_kill = (f_H / Φ) × log₁₀(Z_v + 1)
4. **Zeta estimate:** ζ = −15 − 10·sin(f_kill × 10⁶ × t_pixel)

Constants: f_H = 1420.405 MHz · Φ = 1.194797 · K_ASB = 0.013829 · t_pixel = 3.41×10⁻⁷ s.
Implemented and self-verified in `tools/qag_core.py`.

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## Slide 6 — Worked example: SARS-CoV-2

PDB 6VXX — spike glycoprotein, closed state. 438.26 kDa, 23,694 atoms.
ρ = 0.0185 → Z_v = 586.2 → **f_kill = 3291.5897 MHz** (S-band).
The engine reproduces the registry value to 4 decimal places. *(Run `python tools/qag_core.py` live.)*

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## Slide 7 — The data pipeline

Public structural data in, frequencies out. `tools/qag_pdb_sync.py` queries the RCSB Protein Data Bank API for any PDB ID, extracts molecular weight and atom count, and runs the QAG analysis. No private data, no wetlab — everything downstream of public structural biology.

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## Slide 8 — The species labs

The lab runs across genera and species, each with its own notebook series in `colab/`:
- **K9Virology** — canine
- **FelineVirology** — feline
- **BovineVirology** — bovine
- **QAG Viral V2 / Virology Node / Ingestion Node** — human & general

Same engine, different structural inputs.

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## Slide 9 — The target registry

`data/` holds the computed registries: the 5-target decoherence index, the 11-target virology database, the 38-target research platform (RESPIRATORY, VECTOR_BORNE, ENTERIC, HEMORRHAGIC, CHRONIC, NEUROTROPIC), and the machine-readable 30-target master pathogen index (JSON). Every row: impedance, disruptive frequency, zeta estimate, host safety margin.

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## Slide 10 — The safety frequency

The concept the public repo description names: *"maintaining a safety data frequency."* Each target carries a host safety margin (mV) and a safety lock. The model only transmits where the margin holds — resonance aimed at the pathogen, not the host. *(This is the theoretical core of the "kill switch" framing.)*

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## Slide 11 — The RF stage (theory)

For the primary target (3.2916 GHz), the blueprint derives an analytical L-matching network: 20 − j15 Ω → 50 Ω, C_p = 1.2 pF, L_total = 1.91 nH, VSWR 1.0054. Computed live by `tools/qag_rf_matcher.py`. Presented as theoretical engineering — the SDR signal-chain notes live in `docs/`.

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## Slide 12 — Demo it live

1. `index.html` — guided tour + interactive f_kill calculator
2. `python tools/qag_core.py` — engine self-check
3. `demo/QAGRTE.html` / `demo/ViralQAGv2.html` — dashboards
4. `colab/` — the species notebook series

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## Slide 13 — Roadmap

- Expand the PDB sync to full biological assemblies (QAG_Viral_Ingestion_Node direction)
- Waveform engine v3 (`QAG_Wavev2` / `QAGWaveV3` notebooks in `colab/`)
- Real-time field suite (`docs/QAG_Real-Time_Field_Suite.pdf`)
- Keep every target's safety margin the gating condition

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## Slide 14 — Standing note

This is theoretical and computational research: frequencies computed from public protein-structure data under the QAG framework. Not medical advice, not a treatment protocol, not a device build guide.