Pulse oximetry is an essential tool that saves lives: a call for standardisation
Bibliographic record
Abstract
Pneumonia is a leading global cause of morbidity and mortality, particularly amongst adults aged >70 years and children. Annual deaths due to pneumonia in these groups was estimated at more than one million and 672 000 worldwide for both groups, respectively, in 2019 [1]. The importance of pneumonia is highlighted by impact of the current coronavirus disease 2019 (COVID-19) pandemic on vulnerable populations. Yet, despite the high impact of pneumonia worldwide, diagnosing pneumonia, especially in children in low- and middle-income countries, remains a big challenge. Frequent clinical signs of pneumonia (cough and difficult or rapid breathing) are non-specific and can overlap with other prevalent diseases in these settings, such as malaria. Equally important, data provided by the World Health Organization (WHO) revealed that 40% of children with pneumonia symptoms in the 40 countries reporting 90% of child pneumonia deaths never receive medical care for their pneumonia [2]. Furthermore, overdiagnosis of bacterial pneumonia and unnecessary administration of antibiotics poses an extra challenge, particularly in countries with limited resources for diagnostic procedures. A call to action to immediately review the accuracy of pulse oximeters so that all patients receive optimal and equitable diagnosis and treatment for hypoxaemia <https://bit.ly/2RSPDCT>
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".