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Scientific Evidence & Source Legend

This file documents the scientific and technical sources used to shape IINTS-AF defaults, validation targets, report framing, local AI setup guidance, and best-effort device emulation notes.

Scope: - Pre-clinical simulation and retrospective forecasting only. - Not a treatment recommendation engine. - Not a medical device.

Use iints sources to print the packaged source manifest from the installed SDK.

How To Read This Legend

There are two source buckets in this project:

  1. Packaged evidence sources These are the core medical and dataset references shipped with the SDK and exposed through iints sources.

  2. Documentation-only implementation sources These are the additional references used in the guides for:

  3. Ollama setup
  4. local open Mistral model selection
  5. best-effort device emulation context

That split is intentional: - the packaged manifest stays focused on repeatable research evidence - this page stays readable as the full legend for humans

Category Legend

Category Meaning
guideline formal standards or standards-of-care style guidance
consensus expert consensus used for interpretation targets
trial clinical or comparative outcome study
pharmacology insulin PK/PD reference
sensor CGM behavior, lag, or sensor interpretation source
model mathematical or simulator foundation source
dataset public dataset provenance source
runtime technical runtime or installation reference for local AI
model_card model-family reference for local Mistral choices
regulatory manufacturer or regulator-facing system reference
technical_manual user guide or product documentation
clinical_trial named trial registry or trial program page

How Sources Map to SDK Components

SDK area Why it exists Source IDs
Validation targets (TIR, TBR, TAR, hypoglycemia framing) Keep benchmark interpretation aligned with accepted diabetes metrics ada_2026_glycemic_goals, attd_2019_time_in_range
CGM + AID context in docs/reports Keep language aligned with current standards for technology use ada_2026_diabetes_technology
AID benchmark envelopes Compare algorithm behavior against realistic closed-loop outcomes nejm_2019_control_iq, adapt_2022_ahcl
Meal timing / pre-bolus scenarios Avoid unrealistic meal-response assumptions cobry_2010_meal_bolus_timing
Insulin action profiles (rapid and ultra-rapid) Parameterize onset/peak assumptions from pharmacology literature heise_2017_fiasp_pkpd, klaff_2020_urli_pkpd
Input validation and CGM lag rationale Keep signal handling biologically plausible wentholt_2004_cgm_lag
Virtual patient meal dynamics Ground meal disturbance dynamics in established models dalla_man_2007_meal_model
Simulator realism/validation framing Align in-silico model evaluation with accepted simulator literature visentin_2018_uvapadova
Exercise stress scenarios Use consensus guidance for exercise-related glucose behavior riddell_2017_exercise_consensus
Forecast training data provenance Use publicly documented dataset references marling_2020_ohiot1dm
Local AI setup and model selection docs Keep Ollama and open Mistral setup instructions grounded in official docs ollama_linux_install, mistral_2025_ministral_3_announcement, mistral_2025_ministral_3_3b, mistral_2025_ministral_3_8b, mistral_2025_ministral_3_14b
Device emulation notes Provide best-effort references behind 780G / Control-IQ / Omnipod 5 approximations bergenstal_2020_780g, fda_k193510_780g, medtronic_780g_user_guide, brown_2019_control_iq_dtt, fda_k191289_control_iq, idcl_nct03563313, control_iq_user_guide, assert_omnipod_5, onset_omnipod_5, fda_k203467_omnipod5, omnipod5_user_guide

Packaged Medical And Dataset Sources

  1. ada_2026_glycemic_goals
    ADA Professional Practice Committee. Glycemic Goals and Hypoglycemia: Standards of Care in Diabetes—2026.
    DOI: 10.2337/dc26-S006

  2. ada_2026_diabetes_technology
    ADA Professional Practice Committee. Diabetes Technology: Standards of Care in Diabetes—2026.
    DOI: 10.2337/dc26-S007

  3. attd_2019_time_in_range
    Battelino T, Danne T, Bergenstal RM, et al. Clinical Targets for Continuous Glucose Monitoring Data Interpretation. Diabetes Care. 2019.
    DOI: 10.2337/dci19-0028

  4. nejm_2019_control_iq
    Brown SA, et al. Six-Month Randomized, Multicenter Trial of Closed-Loop Control in Type 1 Diabetes. N Engl J Med. 2019.
    DOI: 10.1056/NEJMoa1907863

  5. adapt_2022_ahcl
    Benhamou PY, et al. Advanced hybrid closed loop therapy versus conventional treatment in adults with type 1 diabetes (ADAPT). Lancet Diabetes Endocrinol. 2022.
    DOI: 10.1016/S2213-8587(22)00212-1

  6. cobry_2010_meal_bolus_timing
    Cobry E, et al. Timing of Meal Insulin Boluses to Achieve Optimal Postprandial Glycemic Control. J Diabetes Sci Technol. 2010.
    DOI: 10.1177/193229681000400404

  7. heise_2017_fiasp_pkpd
    Heise T, et al. A Faster-Onset Formulation of Insulin Aspart. Clin Pharmacokinet. 2017.
    DOI: 10.1007/s40262-017-0510-8

  8. klaff_2020_urli_pkpd
    Klaff LJ, et al. Ultra Rapid Lispro Demonstrates Accelerated Pharmacokinetics and Pharmacodynamics. Diabetes Obes Metab. 2020.
    DOI: 10.1111/dom.14049

  9. wentholt_2004_cgm_lag
    Wentholt IME, et al. How glucose sensors can facilitate therapy in diabetes management. Diabetes Technol Ther. 2004.
    DOI: 10.1089/dia.2004.6.615

  10. dalla_man_2007_meal_model
    Dalla Man C, Rizza RA, Cobelli C. Meal simulation model of the glucose-insulin system. IEEE Trans Biomed Eng. 2007.
    DOI: 10.1109/TBME.2007.893506

  11. visentin_2018_uvapadova
    Visentin R, et al. The University of Virginia/Padova Type 1 Diabetes Simulator Matches the 2014 DMMS.R. J Diabetes Sci Technol. 2018.
    DOI: 10.1177/1932296818757747

  12. riddell_2017_exercise_consensus
    Riddell MC, et al. Exercise management in type 1 diabetes: a consensus statement. Lancet Diabetes Endocrinol. 2017.
    DOI: 10.1016/S2213-8587(17)30014-1

  13. marling_2020_ohiot1dm
    Marling C, Bunescu R. The OhioT1DM Dataset for Blood Glucose Level Prediction: Update 2020. CEUR Workshop Proceedings.
    Paper: ceur-ws.org/Vol-2675/paper2.pdf

Documentation-Only Local AI Setup Sources

These are the official references used in the guides for installing Ollama, understanding the local Ministral 3 family, and explaining why the SDK recommends different model sizes for different hardware.

  1. ollama_linux_install
    Ollama. Linux Installation Documentation.
    URL: docs.ollama.com/linux

  2. mistral_2025_ministral_3_announcement
    Mistral AI. Introducing Mistral 3.
    URL: mistral.ai/news/mistral-3

  3. mistral_2025_ministral_3_3b
    Mistral AI Docs. Ministral 3 3B.
    URL: docs.mistral.ai/models/ministral-3-3b-25-12

  4. mistral_2025_ministral_3_8b
    Mistral AI Docs. Ministral 3 8B.
    URL: docs.mistral.ai/models/ministral-3-8b-25-12

  5. mistral_2025_ministral_3_14b
    Mistral AI Docs. Ministral 3 14B.
    URL: docs.mistral.ai/models/ministral-3-14b-25-12

Documentation-Only Device Emulation References

These references are used for the best-effort emulator notes and are not claims of exact proprietary algorithm reproduction.

Medtronic MiniMed 780G

  1. bergenstal_2020_780g
    Bergenstal RM, et al. Safety of a Hybrid Closed-Loop Insulin Delivery System in Patients With Type 1 Diabetes.
    DOI: 10.1056/NEJMoa2003479

  2. fda_k193510_780g
    U.S. FDA. 510(k) K193510 - MiniMed 780G System.
    URL: accessdata.fda.gov

  3. medtronic_780g_user_guide
    Medtronic Diabetes. MiniMed 780G User Guide / Product Documentation.
    URL: medtronicdiabetes.com

Tandem Control-IQ

  1. brown_2019_control_iq_dtt
    Brown SA, et al. Performance of the Tandem t:slim X2 insulin pump with Control-IQ technology in the International Diabetes Closed-Loop trial.
    DOI: 10.1089/dia.2019.0226

  2. fda_k191289_control_iq
    U.S. FDA. 510(k) K191289 - Control-IQ System.
    URL: accessdata.fda.gov

  3. idcl_nct03563313
    ClinicalTrials.gov. International Diabetes Closed Loop Trial.
    URL: clinicaltrials.gov/ct2/show/NCT03563313

  4. control_iq_user_guide
    Tandem Diabetes Care. Control-IQ User Guide / Product Documentation.
    URL: tandemdiabetes.com

Omnipod 5

  1. assert_omnipod_5
    Insulet / Omnipod. ASSERT Trial - Omnipod 5.
    URL: omnipod.com/assert-trial

  2. onset_omnipod_5
    Insulet / Omnipod. ONSET Trial - Omnipod 5 in Type 2 Diabetes.
    URL: omnipod.com/onset-trial

  3. fda_k203467_omnipod5
    U.S. FDA. 510(k) K203467 - Omnipod 5 System.
    URL: accessdata.fda.gov

  4. omnipod5_user_guide
    Insulet / Omnipod. Omnipod 5 User Guide / Product Documentation.
    URL: omnipod.com

Reproducibility Note

For report reproducibility, pair this file with: - run metadata (run_metadata.json) - manifest hashes (run_manifest.json) - dataset lineage fields in research outputs (source_file_sha256, split metadata).

If you want the machine-readable packaged subset, export it with:

iints sources --output-json results/source_manifest.json