Biotinidase activity is affected by both seasonal temperature and filter collection cards
Bibliographic record
Abstract
This study set out to examine pre-analytical factors affecting the frequency of positive results in newborn screening for biotinidase deficiency. This investigation was prompted by an increase in the annual screen positive rate for biotinidase deficiency in Ontario from 2.65x10−4 in 2016 to 6.57x10−4 in 2017. Season and trend decomposition was used to separate seasonality from an underlying trend in the time series of biotindase activity measurements for the period 2014–01-12 to 2019–07-27 (n = 798,770). This analysis revealed a marked seasonal effect (winter = median + ⩽ 17 MRU, summer = mean - ⩽20 MRU) and a non-linear negative trend. Seasonal temperature was correlated with biotinidase results (Pearson’s r = 0.79) but not with the observed negative trend (Pearson’s r = 0.0025). Time series analysis of biotinidase results grouped by print lot of filter paper revealed that recently printed filter paper cards inhibit biotinidase and that this inhibition resolved over time. This study demonstrates that biotindase activity is inhibited by both increased seasonal temperature and collection on newly printed filter cards.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".