Value-based healthcare delivery through metabolomics-based personalized health platform
Bibliographic record
Abstract
Type 2 diabetes is routinely identified in clinical practice by tests that rely on a hyperglycemic index. However, people at risk for developing type 2 diabetes may not present with hyperglycemia. We identified several underlying risks for type 2 diabetes, insulin resistance, and associated co-morbidities, using a liquid chromatography mass spectrometry-based analysis of blood metabolites, in participants with normoglycemia and no clinical symptoms. Personalized lifestyle recommendations, including diet, exercise, and nutritional supplement recommendations, were conveyed to these participants by a web-based platform, and after 100 days of following their recommendations, these participants reported reductions in the health risks associated with type 2 diabetes and associated diseases. Our comprehensive metabolite-based assay can be used for type 2 diabetes risk stratification, and our personalized lifestyle recommendation system could be deployed as a preventative treatment option to improve health outcomes, reduce the incidence of chronic disease, and live healthier lives in an evidence-based way.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".