Bibliographic record
Abstract
In the 1920s, guanidine, the active component of Galega officinalis, was shown to lower glucose levels and used to synthesize several antidiabetic compounds. Metformin (1,1 dimethylbiguanide) is the most well-known and currently the only marketed biguanide in the United States, United Kingdom, Canada, and Australia for the treatment of non-insulin-dependent diabetes mellitus. Although phenformin was removed from the US market in the 1970s, it is still available around the world and can be found in unregulated herbal supplements. Adverse events associated with therapeutic use of biguanides include gastrointestinal upset, vitamin B 12 deficiency, and hemolytic anemia. Although the incidence is low, metformin toxicity can lead to hyperlactatemia and metabolic acidosis. Since metformin is predominantly eliminated from the body by the kidneys, toxicity can occur when metformin accumulates due to poor clearance from renal insufficiency or in the overdose setting. The dominant source of metabolic acidosis associated with hyperlactatemia in metformin toxicity is the rapid cytosolic adenosine triphosphate (ATP) turnover when complex I is inhibited and oxidative phosphorylation cannot adequately recycle the vast quantity of H+ from ATP hydrolysis. Although metabolic acidosis and hyperlactatemia are markers of metformin toxicity, the degree of hyperlactatemia and severity of acidemia have not been shown to be of prognostic value. Regardless of the etiology of toxicity, treatment should include supportive care and consideration for adjunct therapies such as gastrointestinal decontamination, glucose and insulin, alkalinization, extracorporeal techniques to reduce metformin body burden, and metabolic rescue.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".