Early recognition and management of brain tumours in children
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Brain tumours comprise over one quarter of all childhood cancers in the UK and are the most common cause of cancer-related deaths in children. The presentation of brain tumours can vary substantially in children. The presenting symptoms are often similar to less serious conditions, and are often managed as such initially. Therefore, it can be difficult to diagnose brain tumours in children. An early diagnosis is usually associated with more effective treatment and improved health outcomes. The diagnostic interval between first presentation to a health professional and diagnosis for brain tumours in children has been shown to be three times longer in the UK than in other developed countries. As a result, the HeadSmart campaign launched a symptom card in 2011 to increase awareness of brain tumours in children among the general population and healthcare professionals, with the aim of reducing the diagnostic interval to 5 weeks. Nurses have an essential role in early recognition of brain tumours in children, and in providing care and support to the child and their family following a diagnosis.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it