Plasma YKL-40 in Inuit and Danes
Bibliographic record
Abstract
AIMS: The aim of the present study was to investigate whether there are differences in plasma levels of YKL-40 between Inuit in Greenland and in Denmark and in Danes, as well as to study the relationship between alcohol intake, plasma YKL-40 and other factors in Inuit. METHODS: Plasma YKL-40 levels were measured on 1645 people from The Greenland Population Study (a cross-sectional population study of Inuit from Denmark and West Greenland) and were compared with the plasma YKL-40 levels of 8899 people from The Copenhagen City Heart Study (a population-based, prospective study of the Danish general population). RESULTS: The plasma concentrations of YKL-40 were significantly (P = 0.001) lower in Inuit living in Greenland (median 46 µg/l, range 10-2164, n = 1164) compared with the plasma YKL-40 levels of Inuit living in Denmark (median 63 µg/l, range 20-2827, n = 481) and of Danes living in Denmark (median 55 µg/l, range 10-2909, n = 8899). In Inuit, increased alcohol intake was significantly associated with increased plasma YKL-40 levels (P < 0.001), and high plasma YKL-40 levels were associated with high values of alkaline phosphatase and low values of albumin. Smoking, gender and bilirubin were not associated with the plasma YKL-40 level. High levels of YKL-40 and alcohol were associated with where people lived. CONCLUSION: The plasma concentrations of YKL-40 are significantly lower in Inuit living in Greenland than Inuit and Danes living in Denmark. A number of factors, including different alcohol intake patterns, nutrition and genes may play a role in these findings.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".