The mutation spectrum of hyperphenylalaninaemia in the Republic of Ireland: the population history of the Irish revisited
Bibliographic record
Abstract
Phenylketonuric and hyperphenylalaninaemic patients in the population of the Republic of Ireland were screened for mutations at the human phenylalanine hydroxylase (PAH) locus. A composite data set for the island of Ireland was generated by merging the findings of this study with extant data for Northern Ireland. Analysis of this data on the basis of the four historic provinces (Munster, Leinster, Connacht and Ulster) revealed genetic diversity that is informative in terms of demographic forces that shaped the Irish population. R408W, the predominant Irish PAH mutation associated with haplotype 1.8, reached its highest relative frequency in the most westerly province, Connacht. This suggests that the gradient of R408W-1.8 observed across north-western Europe continues into Ireland and peaks in Connacht. Spatial autocorrelation analysis demonstrated that the gradient is consistent with a localised cline of R408W-1.8 likely to have been established by human migration. This and parallel allele frequency clines may represent the genetic traces of the Palaeolithic colonisation of Europe, a pattern not substantially altered in north-western Europe by subsequent Neolithic migrations. An analysis of mutant allele distributions in Ulster, Scotland and the rest of Ireland confirmed that Ulster has been a zone of considerable admixture between the Irish and Scottish populations, indicating a proportion of Scottish admixture in Ulster approaching 46%. Mutations primarily associated with Scandinavia accounted for 6.1% of mutations overall, illustrating the influence of Viking incursions on Irish population history.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".