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Claim-to-Evidence Map

This page tells a reviewer where to verify each important statement. A claim is strong only when its implementation, test, output and scientific basis are kept separate.

Core project claims

Claim Implementation Verification or output Boundary
The SDK simulates virtual diabetes scenarios src/iints/core/simulator.py, src/iints/core/patient/ Core, scenario and preset tests; results.csv Research approximation
Candidate actions pass a separate safety layer src/iints/core/supervisor.py, src/iints/core/safety/ Safety tests, audit events and safety report Not proof of clinical safety
Physiology is deterministic code, not LLM output src/iints/core/formula_registry.py, patient model _ode methods Formula registry tests and numeric-authority checks Parameter validity still matters
CGM can differ from latent glucose src/iints/core/devices/models.py Sensor tests and separate result columns Generic, not vendor-equivalent
Runs produce inspectable evidence src/iints/highlevel.py, src/iints/analysis/, src/iints/validation/ CSV, metadata, manifests, reports Artifact set varies by command
Data can be contract-checked src/iints/data/ MDMP certificate and quality report Certification is not clinical approval
AI is advisory in explanation mode src/iints/ai/, docs/NUMERIC_AUTHORITY.md Prompt/policy tests and separate AI artifacts Human review remains required
Desktop app calls the same SDK apps/iints-tauri/, src/iints_desktop/ Rust checks, bridge tests and desktop smoke tests Packaging/security need maintenance
Edge and FPGA paths are bench-only src/iints/live_patient/, src/iints/jetson/ Mock, protocol and hardware-adapter tests No medication actuation

Formula evidence map

Runtime paths in this table are relative to src/iints/core/.

ID Runtime authority Scientific basis
F01 Bergman glucose patient/bergman_model.py Bergman 1979 plus declared extensions
F02 remote insulin patient/bergman_model.py Bergman 1979
F03 plasma insulin patient/bergman_model.py Bergman balance plus disabled-by-default research secretion
F04 subcutaneous insulin Bergman and Hovorka patient models Hovorka 2004 and PK abstraction
F05 meal absorption Bergman and Hovorka patient models Published Hovorka two-compartment chain; explicitly adapted three-stage Bergman branch
F06 Hovorka glucose mass patient/hovorka_model.py Hovorka 2004 plus declared extensions
F07 insulin-action channels patient/hovorka_model.py Hovorka 2004 action channels plus heuristic molecular/tissue sensitivity scalars
F08 stress/exercise patient/hovorka_model.py Research pseudo-hormone abstraction
F09 GLUT4/NIMGU patient/hovorka_model.py Exercise/GLUT4 physiology context
F10 circadian EGP patient/hovorka_model.py Dawn-phenomenon context, gated approximation
F11 hypo rescue Bergman and Hovorka patient models Counterregulation and HAAF context
F12 HAAF memory Bergman and Hovorka patient models Cryer 2013, experimental memory state
F13 glucagon PK/PD Bergman and Hovorka patient models Published exogenous-glucagon context
F14 renal clearance patient/physiology.py and both ODE models Renal threshold/splay context
F15 CGM observation devices/models.py, SensorModel.read Blood-to-ISF lag and sensor context

Canonical source: src/iints/core/formula_registry.py. Generated human reference: docs/FORMULA_REGISTRY.md.

Benchmark evidence map

Paths in this table are relative to research/eucys_pack/, except where noted. The named study runner lives in tools/research/.

Evidence Repository path Review question
Aggregate arm table assets/EUCYS_RESULTS_TABLE.csv Do arm counts and metrics match the report?
Algorithm figure data assets/EUCYS_MAIN_FIGURE.csv Can every plotted bar be reconstructed?
Main figure assets/EUCYS_MAIN_FIGURE.png Does visual labelling match the table?
Full report source ../EUCYS_REPORT.md Are protocol, results and limitations stated?
Final workflow ../EUCYS_FINAL_WORKFLOW.md Can the benchmark and report be regenerated?
Study runner run_eucys_final.sh Is the command path explicit?

Scientific source map

Topic Primary source used in SDK documentation
Glycaemic targets and hypoglycaemia ADA Standards of Care 2026, DOI 10.2337/dc26-S006
Time in range Battelino et al. 2019, DOI 10.2337/dci19-0028
Bergman minimal model Bergman et al. 1979, DOI 10.1152/ajpendo.1979.236.6.E667
Hovorka model Hovorka et al. 2004, DOI 10.1088/0967-3334/25/4/010
Meal absorption Dalla Man et al. 2007, DOI 10.1109/TBME.2007.893506
CGM lag Wentholt et al. 2004, DOI 10.1089/dia.2004.6.615
Exercise in T1D Riddell et al. 2017, DOI 10.1016/S2213-8587(17)30014-1
Exercise and GLUT4 Richter and Hargreaves 2013, DOI 10.1152/physrev.00038.2012
HAAF Cryer 2013, DOI 10.1056/NEJMra1215228
Renal glucose handling Hummel et al. 2018, DOI 10.1007/s00125-018-4656-5
OhioT1DM Marling and Bunescu 2020, CEUR paper
AGP interpretation International Diabetes Center guide and TIR consensus

The complete maintained source list is in docs/EVIDENCE_BASE.md and docs/SOURCE_LIBRARY.md.

Mermaid diagram sources

The diagrams in this dossier are both embedded in the Markdown pages and stored as reusable Mermaid source:

Diagram Source
System architecture docs/eucys/diagrams/system-architecture.mmd
Simulation step docs/eucys/diagrams/simulation-step.mmd
Numeric authority docs/eucys/diagrams/numeric-authority.mmd
Evidence lifecycle docs/eucys/diagrams/evidence-lifecycle.mmd
Desktop bridge docs/eucys/diagrams/desktop-bridge.mmd
AI boundary docs/eucys/diagrams/ai-boundary.mmd
Data lifecycle docs/eucys/diagrams/data-lifecycle.mmd
Cross-scale evidence docs/eucys/diagrams/cross-scale-evidence.mmd
Validation ladder docs/eucys/diagrams/validation-ladder.mmd

Reproduction commands

Build this dossier:

tools/research/build_eucys_dossier.sh

Build the existing evidence PDFs:

tools/research/build_eucys_pack.sh

Run the final benchmark workflow:

tools/research/run_eucys_final.sh \
  --algo algorithms/example_algorithm.py \
  --output-dir results/eucys_2026 \
  --seeds 1,2,3,4,5,6,7,8,9,10 \
  --no-prepare-ai

Build and validate the documentation:

mkdocs build --strict

Run the principal software checks:

python3 tools/ci/check_architecture_boundaries.py
python3 -m pytest tests/ -q
mypy src/iints/

Review checklist

A reviewer should be able to trace:

  1. A sentence in the report to a table or raw trace.
  2. A table value to deterministic metric code.
  3. A simulated state to a registered equation and parameter set.
  4. A safety intervention to a candidate, accepted action and reason.
  5. A dataset to a source and transformation manifest.
  6. An AI statement to supplied evidence.
  7. A biological context view to its public source and interpretation boundary.
  8. A release artifact to a tagged software version.