98 JOURNAL OF PUBLIC HEALTH Concerning: Screening for tuberculosis: more to be done
Bibliographic record
Abstract
We read with great interest the study of Brewin et al.1 regard-ing the important topic of the level of acceptability of screen-ing for tuberculosis among immigrants. However, we would like to make some comments on the methodology followed by the authors and on the validity of the results. According to the authors, there was a significant level of acceptability of screening, because only four individuals interviewed declined it for various reasons. It would be inter-esting if the authors reported the relative frequency of the subjects who agreed to participate in the screening procedure during the period of the screening offer. Although the authors claim that their findings are novel, there are previ-ously published studies that report acceptability rates. In a primary care clinic for refugee claimants in Canada, Levesque et al.2 describe that 76.7 % of the participants accepted tuber-culin skin test. In another study3 which was conducted by a social worker and non-governmental organization in Bilbao, Spain, the participation ratio was 75.4%. Carvalho et al.4 reported that although screening for latent tuberculosis infection was offered to 649 undocumented immigrants, only 33 % of them accepted it. It is also noteworthy that the samples of the aforementioned studies consisted of>200 subjects. Brewin et al. used a constant comparison approach to search for deviant cases and thus strengthen the validity of their results. However, even though grounded theory is widely used and has specific advantages, we believe that the integration of a qualitative method in the study would add to its validity.5 The sample of the study does not seem to represent prop-erly the distribution of the countries of origin of the immi-grants living in the United Kingdom.6 For example, although immigrants coming from Pakistan formed 7.85 % of all immi-grants entering the United Kingdom in 2004 (except for
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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 | 0.016 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.016 | 0.012 |
| Insufficient payload (model declined to judge) | 0.045 | 0.008 |
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".