Variation in haemoglobin measurement across different HemoCue devices and device operators in rural Cambodia
Bibliographic record
Abstract
: Point-of-use haemoglobinometers, such as the HemoCue, are a common method to measure haemoglobin (Hb) concentration in field settings as the device is portable, requires only a small finger-prick capillary blood sample and computes an immediate Hb reading. The aim of this study was to compare Hb measurements across different HemoCue devices and across device operators using capillary blood samples collected from women during a trial in rural Cambodia. We compared mean±SD capillary Hb concentration (g/L) across n=12 different HemoCue Hb 301 devices and across n=9 device operators among 2846 Cambodian women. Significant variability in mean Hb concentration was observed across HemoCue devices (means ranged from 117 to 124 g/L) and across device operators (means ranged from 118 to 124 g/L). This variability is of particular concern when a single HemoCue device or device operator is used at different time points in surveys or research trials. TRIAL REGISTRATION NUMBER: NCT02481375.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".