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📐 Data Schema

Source-of-truth tables powering all pages. S3: s3://edicer-dev-mindnetq-ledger/inventory/

Entity Relationship

┌─────────────────────┐       ┌─────────────────────┐
│ compound_inventory   │       │   product_table      │
│ (338 records)        │       │   (28 products)      │
├─────────────────────┤       ├─────────────────────┤
│ id (PK)             │◄──────│ therapeutics[].target │
│ smiles (UNIQUE)     │       │ id (PK: MNQP/S/A/T/D)│
│ target (FK→product) │       │ category             │
│ priority            │       │ name                 │
│ stage               │       └──────────┬──────────┘
│ vina_score          │                  │
│ qed, mw            │                  │ 1:N
└─────────────────────┘                  ▼
                              ┌─────────────────────┐
                              │   pricing_table      │
                              │   (43 line items)    │
                              ├─────────────────────┤
                              │ id (FK→product)      │
                              │ tier                 │
                              │ price                │
                              │ unit                 │
                              └─────────────────────┘

┌─────────────────────┐       ┌─────────────────────┐
│  model_registry      │       │  quantum_registry    │
│  (47 models)         │       │  (EQCF framework)    │
├─────────────────────┤       ├─────────────────────┤
│ id (PK)             │       │ qptm.results[]       │
│ name                │       │ delta_q.results[]    │
│ category            │       │ vqe_batch.results[]  │
│ algorithm           │       │ eqcf_gate.results[]  │
│ status              │       │ methods[]            │
│ code                │       │ roadmap[]            │
└─────────────────────┘       └─────────────────────┘

┌─────────────────────────────────────────────────────┐
│  product_inventory_joined (MATERIALIZED VIEW)        │
│  = product_table + compound_inventory embedded       │
│  therapeutics[].compounds[] = full compound records   │
└─────────────────────────────────────────────────────┘

compound_inventory.json

338 records · Key: id · Unique constraint: smiles

Field	Type	Required	Description
id	string	✅	Compound identifier (e.g. CRYZ-021, EGEN-H1, GC-0045)
smiles	string	✅	SMILES structure (unique index, no duplicates)
target	string	✅	Gene target: METAP1D \| CRYZ \| ATP1A4 \| BRD4
vina_score	float\|null	—	AutoDock Vina binding score (kcal/mol, lower=better)
qed	float\|null	—	Quantitative Estimate of Drug-likeness (0-1)
mw	float\|null	—	Molecular weight (Daltons)
stage	enum	✅	wet_lab_ready \| advanced_validated \| grade_a \| parked \| candidate
priority	enum	✅	HIGH \| MEDIUM \| LOW \| UNRANKED
next_step	string\|null	—	Next action for this compound
commercial_priority	string\|null	—	Commercial ranking
gene_group	string\|null	—	Gene group classification
source	string\|null	—	Generation source (GenChem, manual, etc.)
validation	string\|null	—	Validation status
strain	string\|null	—	Strain data
evidence_chain	string\|null	—	Hash-chained evidence reference

product_table.json

28 products · Key: products.[category].[].id

Field	Type	Description
id	string	Product ID (MNQP-001, MNQS-002, MNQA-003, MNQT-METAP1D, MNQD-001)
name	string	Product name
category	enum	Platform \| Service \| Access Tier \| Therapeutic \| Diagnostic
type	string	Sub-type description
pricing_model	string	Monthly \| Annual \| Fixed \| Per-seat \| Project-based
price_range	string	Human-readable price
description	string	Product description
timeline	string\|null	Delivery timeline (services only)

Categories: platform (3) · services (9) · platform_access (5) · therapeutics (4) · diagnostics (7)

pricing_table.json

43 line items · Key: id + tier (composite)

Field	Type	Description
id	string	FK → product_table.id
product	string	Product name
category	enum	Platform \| Access \| Service \| Therapeutic \| Diagnostic
tier	string	Pricing tier (Standard, Enterprise, Eval, License, etc.)
price	int\|null	Price in USD (null = "Contact")
price_min	int\|null	Range minimum (for variable pricing)
price_max	int\|null	Range maximum
price_annual	int\|null	Annual recurring (for license + annual models)
unit	string	month \| year \| project \| fixed \| eval \| upfront + royalty
notes	string	What's included at this tier

model_registry.json

47 models · Key: categories.[group].[].id

Field	Type	Description
id	int	Model number
name	string	Model name
algorithm	string	Algorithm/architecture description
code	string	Source file path
status	enum	Active \| API \| Built \| Wired \| NEW \| Planned
training	string	Training data description
weights	string	Model weights / performance metrics
details	object\|null	Extended details (BioMistral only)
when	string\|null	Planned trigger (planned models only)

Groups: mindnetq_governance (8) · edice_core (7) · edice_r_research (7) · edice_brain (1) · drug_discovery (14) · mindads (7) · planned (8)

quantum_registry.json

EQCF framework · Nested structure

Section	Type	Records	Description
qptm.results[]	array	3	5-dimension perturbation tensor per compound
delta_q.results[]	array	6	Classical-quantum agreement (ΔQ)
vqe_batch.results[]	array	7	VQE validation results per hero
eqcf_gate.results[]	array	3	6-criteria confirmation gate
benchmark.methods[]	array	3	Method comparison
roadmap[]	array	7	QPU roadmap phases
methods[]	array	9	Quantum methods used
patent.claims[]	array	4	Patent claims (17-20)

CIFOG Tables (Planned)

Cortex Integrated Fused Omics Graph · Vector + DynamoDB + S3

Table / Store	Type	Key	Purpose
cifog-nodes (OpenSearch)	Vector index	entity:context (e.g., KRAS:PAAD)	256-dim fused omics embeddings, GCN-produced
cifog-edges (OpenSearch)	Edge index	source:target:type	Explicit validated cross-modal interactions
cifog-state (S3)	Object store	s3://cifog-state/{entity}/{context}/v{n}.cbor	Full per-modality raw state + provenance
cifog-gcn-weights (S3)	Model artifact	s3://cifog-state/models/gcn_v{n}.pt	Trained GCN parameters (classical)
cifog-outcomes (DynamoDB)	Key-value	pk=outcome:{id}	Validation outcomes feeding GCN retraining

Fused Node Schema (Vector Index)

Field	Type	Description
id	string	entity:context (e.g., "KRAS:PAAD")
embedding	float[256]	GCN-produced fused omics vector
classification	enum	DRIVER \| PASSENGER \| RESISTANCE \| SYNTHETIC_LETHAL \| EPIGENETIC
actionability	float	0.0-1.0
mechanism	string	Best intervention mechanism
authority	float	0.0-1.0 (earned from outcomes, decays)
n_validations	int	Times confirmed by outcomes
last_validated	timestamp	Most recent outcome confirmation
origin	enum	prior \| constructed \| learned \| quantum_discovered
shard	string	Cancer type shard (paad, brca, luad, ...)

Fused Edge Schema

Field	Type	Description
source_id	string	Source fused node ID
target_id	string	Target fused node ID
edge_type	enum	co_driver \| synthetic_lethal \| resistance \| pathway_cascade
fused_weight	float	Cross-modal interaction strength
causal_confidence	float	Mechanistic vs correlational
gcn_activation_avg	float	Average GCN filter activation across predictions
origin	enum	prior \| learned \| quantum_discovered \| gcn_discovered
evidence_hash	string	SHA-256 chain pointer

Sharding

Shard	Content	Est. Nodes	Sub-Shards
cifog-paad	Pancreatic adenocarcinoma	~500	mapk, pi3k, chromatin
cifog-brca	Breast cancer	~600	er, her2, tnbc
cifog-luad	Lung adenocarcinoma	~450	egfr, alk, kras
cifog-prad	Prostate cancer	~400	ar, dna_repair, neuroendocrine
cifog-global	Pan-cancer (nodes in ≥3 shards)	~150	—

Storage Locations

File	Local Path	S3 Path	Encryption
compound_inventory.json	edice-r-prad/results/	s3://edicer-dev-mindnetq-ledger/inventory/	KMS
product_table.json	edice-r-prad/results/	s3://edicer-dev-mindnetq-ledger/inventory/	KMS
pricing_table.json	edice-r-prad/results/	s3://edicer-dev-mindnetq-ledger/inventory/	KMS
model_registry.json	edice-r-prad/results/	s3://edicer-dev-mindnetq-ledger/inventory/	KMS
quantum_registry.json	edice-r-prad/results/	s3://edicer-dev-mindnetq-ledger/inventory/	KMS
product_inventory_joined.json	edice-r-prad/results/	s3://edicer-dev-mindnetq-ledger/inventory/	KMS

HTML Pages (Generated from JSON)

Page	Source Table(s)	Regenerate Command
index.html	compound_inventory	Counts, targets, priorities
heroes.html	compound_inventory	Top compounds by priority
discovery.html	compound_inventory	Programs by target
products.html	pricing_table + product_table	Full pricing sheet
catalog.html	product_inventory_joined	All products + compounds
models.html	model_registry	47 models by category
quantum.html	quantum_registry	EQCF, QPTM, VQE, methods
arch.html	—	Static (architecture diagrams)
investor.html	compound_inventory + pricing_table	Counts + revenue projections
gates.html	—	Static (gate definitions)
pharma.html	product_table + pricing_table	Licensing + kits
wetlab.html	—	Static (protocol)
sentinel.html	—	Static (security config)
schema.html	—	This page

Site Map

#	Page	Link	Content
1	Index	index.html	Hub — stats, targets, products
2	Heroes		Top compounds with scores
3	Discovery	discoveries.html	Drug programs by target
4	Architecture	arch.html	System diagrams, data flow, SMOS, CIFOG
5	🧬 CIFOG	cifog.html	Fused Omics Graph — GCN, sharding, lifecycle
6	Investor	investor.html	Market, milestones, revenue, ask
7	Gates	gates.html	Pipeline gates, authority contraction
8	Models	models.html	Model registry (from DynamoDB)
9	Pharma	pharma.html	Licensing, kits, services
10	Quantum	quantum.html	EQCF, QPTM, VQE, methods
11	Wet Lab	wetlab.html	Protocol, budget
12	Sentinel	sentinel.html	Security, CVE scan, brain arch
13	Products	products.html	Full pricing sheet
14	Catalog	catalog.html	Joined product + inventory
15	Schema	schema.html	This page — data schema + site map
16	NPEAD	npead.html	Scoring engine, MAML, weights
17	Multi-Omics	multiomics.html	7-modality pipeline
18	Cortex Intel	cortex-intel.html	Cortex intelligence dashboard
19	Cortex Docs	cortex-docs.html	Cortex documentation
20	Control	control.html	Control panel
21	Schedules	schedules.html	Cron jobs, nightly cycle
22	Gene Scan	gene-scan.html	Full genome scan results
23	CDx Pathway	cdx-pathway.html	Companion diagnostic pathway
24	Repurposing	repurposing.html	Drug repurposing engine
25	Demo	demo.html	Live demo
26	Pricing	pricing.html	Pricing tiers
27	Revenue	revenue.html	Revenue tracking
28	Landing	landing.html	Public landing page
29	Paper	paper.html	Research papers
30	Report Card	report-card.html	Platform report card
31	Thinking	thinking.html	Strategic thinking
32	Synopsis	synopsis.html	Executive synopsis
33	Workspace	workspace.html	Dev workspace

MindNetQ Data Schema | 6 source tables | 14 HTML pages | All KMS encrypted on S3

Two Entry Points: Cortex (agentic AI — reasons, learns, monitors) + MindNetQ Cortex (governed multi-omics — executes, audits, produces Research Objects). They enrich each other. Every interaction makes both smarter.

RO-Crate Evidence Schema (Repurpose)

Path: s3://edicer-dev-research-objects-865950114883/ro-crates/RO-REPUR-{gene}/ro-crate-metadata.json

@graph Node	@type	Key Fields
ro-crate-metadata.json	CreativeWork	conformsTo: RO-Crate 1.1
./	Dataset	name, identifier, datePublished, engine, engineVersion, integrityHash, hasPart[]
#result	ComputationalResult	target, drug, drugbankId, mechanism, repurposeRationale, predictedVina, grade, decision
#trust	GovernanceTrust	trustLevel, grade, authority, decision, capReason, ledgerHash, roCrateUri
#billing	BillingRecord	gene, drug, mode, internal_cost_usd, retail_price_usd, margin_pct, compute_type
#evidence-chain	EvidenceChain	stepsComplete, steps{step_1..4}: source, action, evidence_hash, tamper_evident
#disclaimer	Disclaimer	text: "COMPUTATIONAL HYPOTHESIS — REQUIRES EXPERT VALIDATION"

De Novo Evidence (same structure)

Path: s3://edicer-dev-research-objects-865950114883/ro-crates/RO-{gene}/ro-crate-metadata.json

@graph Node	@type	Key Fields
#result	ComputationalResult	target, action=gpu_docking, totalCompounds, bestVina, bestSMILES, qed, mw, top5[]
#admissibility-evidence	AdmissibilityEvidence	nimScore, criticConfidence, thresholds{S, sigma_sq, R_theta, R_h}
#trust	GovernanceTrust	pqmStatus, qcmTrust, qdmSubstrate, parityStatus, ledgerHash
#targets	TargetPanel	primaryTarget, totalTargetsHit, targets[]
#billing	BillingRecord	internal_cost_usd, retail_price_usd, compute_type=gpu
#evidence-chain	EvidenceChain	stepsComplete, steps{pre_filters, docking, scoring, governance}
#performance	PerformanceMetrics	totalMs, nimMs, substrateMs, scorer