Evaluation of a continuous glucose monitor-derived homeostasis metric for type 2 diabetes screening
Bibliographic record
Abstract
Abstract Effective intervention for Type 2 Diabetes relies heavily on early detection. However, a majority of people with early-onset diabetes are not aware of their condition and are likely to consult with a physician only when their homeostatic control of blood sugar levels is irreparably damaged. Thus, there is a growing demand for screening tools that can easily be integrated into routine check-ups and do not require changes in daily routine and diet, doctor consults or laboratory analysis of blood samples. The screening tool we propose here is based on data gathered from Continuous Glucose Monitors and on a model of the blood glucose level as a function of glucose intake and the dynamics of the feedback control. We calibrate the method using data from a clinical trial with subjects diagnosed by a physician (n=123) and validate it on a larger follow-up study (n=270). Here we show that the sensitivity of the proposed test is on par with that of the HbA1c criterion and exceeds that of the Oral Glucose Tolerance Test.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".