Analytical report on the feasibility of using ethnic questions for risk status ascertainment in antenatal selective screening for sickle cell and thalassaemia: The findings of a formal trial of candiate questions
Bibliographic record
Abstract
Two candidate evidence-based ethnic/family origin questions were tested in this formal trial to assess their efficacy in ascertaining risk status in selective antenatal screening for sickle cell and thalassaemia. One of these questions (Question A) is a classification question similar in structure to the 2001 Census England and Wales question but with extended categorisation to capture all appropriate risk groups and a “tick all that apply” method (as opposed to categories) to capture mixed heritage; the other (Question B) is an open response ancestry or ethnic/family origins question, similar in type to those used in US and Canadian Censuses, but comprising an initial “screening” question to identify those with ancestors from areas of the world outside of the UK or Republic of Ireland followed by free text provision to write in countries of ethnic/family origin.
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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 | 0.159 | 0.281 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".