Glycemic Control and Hypoglycemia: Is the Loser the Winner?
Bibliographic record
Abstract
The editorial by Perlmuter et al. (1) in the October 2008 issue of Diabetes Care commented on the long-term effects of severe hypoglycemia and raised concerns about our study (2), which reported that within the cohort of subjects who entered the Diabetes Control and Complications Trial (DCCT) during adolescence, there was no relationship between subsequent episodes of severe hypoglycemia and cognitive performance measured ∼20 years after study entry. Below, we outline their five major concerns and provide supporting information. One concern of Perlmuter et al. was the exclusion of potential participants from the DCCT if they had a history of severe hypoglycemia, thus limiting generalizability. However, a history of severe hypoglycemia was not an absolute exclusion criterion for participation in the DCCT. Indeed, 24% of the 175 participants had previously experienced 1–5 episodes of severe hypoglycemia with loss of consciousness before entry …
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.030 | 0.027 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".