Sovereign Sample Provenance

Status: Active | Date: March 13, 2026 Depends on: Papers 04 (Sentinels), 09 (Field Genomics), 16 (Anaerobic QS), 20 (NFT Economics) Validated by: 🎮♨️ ludoSpring exp062_field_sample_provenance (39/39 checks), exp064_beardog_signed_chain (39/39 checks), exp065_cross_domain_fraud (74/74 checks) License: AGPL-3.0-or-later

Abstract

The same provenance architecture that tracks game items tracks biological samples. This paper demonstrates that 🌱🔐 rhizoCrypt DAG + 🪨📖 loamSpine certificate + 🍯🌾 sweetGrass braid + 🐻🐕 BearDog signature provides complete field-to-publication chain-of-custody for scientific samples. Fraud detection reduces to graph analysis — the same code that catches item duplication in gaming catches phantom samples in a laboratory. Every biological sample is a 🧫📜 Novel Ferment Transcript.

1. The Chain-of-Custody Problem

Current State

Scientific chain-of-custody is typically maintained through:

• Paper logbooks (lossy, forgeable)
• Spreadsheet-based LIMS (no cryptographic integrity)
• Proprietary tracking systems (vendor lock-in, closed source)
• Manual compliance reporting (expensive, error-prone)

ISO 17025 and ISO 15189 require traceability but do not prescribe the mechanism. Most labs satisfy the requirement with the minimum viable paper trail.

What’s Missing

The Provenance Trio Solution

Field sample ←──loamSpine cert──► Lab analysis record
                              │
                              ├── rhizoCrypt: Collect → Transport → Store → Extract → Amplify → Sequence → Analyze → Publish
                              ├── loamSpine: custody transfers, condition changes, accession
                              ├── sweetGrass: collector, transporter, technician, analyst, PI attribution
                              └── BearDog: Ed25519 signature on every operation

2. Domain Model

Sample Lifecycle

Every biological sample follows a directed acyclic graph of operations:

Collect ─► Transport ─► Store ─► Extract ─► Amplify ─► Sequence ─► Analyze ─► Publish
   │           │           │         │          │           │           │
   ▼           ▼           ▼         ▼          ▼           ▼           ▼
 [cert]    [custody]   [custody]  [process]  [process]   [process]  [process]

Each node is a 🌱🔐 rhizoCrypt vertex. Each transition is a custody transfer or processing step recorded in the DAG. The 🪨📖 loamSpine certificate carries the sample’s persistent identity — its accession number, sample type, collection metadata, and condition.

Data Types (from exp062)

Mapping to Standards

3. Fraud Detection as Graph Analysis

The Universality Insight

exp065 proves that fraud detection across gaming, science, and medicine reduces to the same five graph patterns:

This is not a metaphor. exp065 runs the same GenericFraudDetector code on DAGs labeled with gaming vocabulary and science vocabulary. The detected fraud types are identical — only the names change.

Sample-Specific Fraud Types (exp062)

4. Cross-Spring Architecture

What wetSpring Gets

exp062 provides a concrete Rust pattern that maps directly to 💧♨️ wetSpring’s existing field genomics architecture (sub_thesis_06):

wetSpring (field genomics)          exp062 (scaffold)
─────────────────────────           ─────────────────
field_sample_collection      ←─►   collect_sample()
sample_transport_log         ←─►   transport()
lab_processing_pipeline      ←─►   process()
publication_record           ←─►   publish()
quality_control_step         ←─►   process(QualityControl)

💧♨️ wetSpring teams adopt the domain model and fraud detectors directly. The 🐻🐕 BearDog-signed chain (exp064) makes every custody transfer cryptographically non-repudiable.

Integration Path

1. 💧♨️ wetSpring reads exp062 as a reference implementation
2. Adapts SampleType and ProcessingStep to their specific pipelines
3. Deploys 🌱🔐 rhizoCrypt + 🪨📖 loamSpine + 🍯🌾 sweetGrass as 🌿🖥️ biomeOS graph services
4. 🐻🐕 BearDog signs every operation via IPC (JSON-RPC over Unix socket)
5. songbird discovers the provenance trio services at runtime
6. The fraud detectors become the automated QC pipeline

5. Radiating Attribution for Science

The Value Chain

When a scientific sample generates value — a publication, a patent, a dataset — the 🍯🌾 sweetGrass attribution chain records every contributor:

Field collector (Creator)
    └── Transport technician (Contributor)
        └── Lab technician (Contributor)
            └── Bioinformatics analyst (Contributor)
                └── Principal investigator (Validator)

exp066 computes the radiating distribution:

This is the sunCloud economic model applied to science: value radiates back through the attribution chain to every contributor. The field collector who spent three days in the mud gets permanent, cryptographically verifiable credit for every publication that uses their sample.

6. Cryptographic Integrity (exp064)

Every operation in the sample lifecycle is signed:

The ProvenanceChainVerifier (exp064) walks the entire chain and verifies every signature. A single tampered vertex is detected at its exact position.

7. Experiment Validation Summary

Total: 193 checks, 0 failures.

8. Connections to Other Papers

9. Future Work

• 💧♨️ wetSpring adoption: Direct integration with field genomics pipeline
• Real 🐻🐕 BearDog signing: Replace model signatures with live IPC
• Public anchor: Optional blockchain anchoring for regulatory proof
• Cross-institution provenance: songbird discovery for multi-lab chains
• ISO 17025 compliance matrix: Formal mapping of all requirements to provenance trio operations