NZSSD: New Zealand Society for the Study of Diabetes WHO: World Health Organization CDA: Canadian Diabetes Association EASD: European Association for the Study of Diabetes Commentary Open Access
Bibliographic record
Abstract
Gestational diabetes mellitus (GDM) is defined as carbohydrate intolerance of varying degrees of severity with onset or first recognition during pregnancy [1]. This clinical entity was first identified in 1957 by Carrington and his colleagues, but the diagnosis of GDM was formalized by John O’Sullivan through the 3-hour 100g glucose tolerance test (OGTT) [2-4]. The authors assessed the distribution of plasma glucose levels in pregnant women, and determined the diagnostic threshold for GDM. The initial rationale for diagnosing GDM was to assess the risk of women in developing post-partum diabetes, but there was also some data linking GDM to adverse pregnancy outcomes [4]. Since then, there had been a number of diagnostic criteria for GDM (Table 1) [5-9]. This had resulted in a great deal of confusion among clinicians, and the lack of standardization of diagnosis of GDM also made it difficult to compare women with GDM between different countries. A number of studies
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.006 | 0.013 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.086 | 0.018 |
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".