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
Headache is common. The lifetime prevalence of headache in the UK general population is over 90% 1 and an estimated 46% of the population are troubled by headache in any one year. eadache accounts for 4.4% of consultations in primary care 3 and 20-30% of neurology out-patient consultations. Nearly all headache is primary, with the majority of patients suffering from tension-type headache, migraine, or both together. Secondary headaches, that is, headaches attributed to another disorder, are rare. There is no diagnostic test for primary headache. Diagnosis is made by taking a good history. The vast majority of patients with headache are managed by GPs, and only 2-3% are referred to neurology services. espite this, GPs seem to be poor at diagnosing headache. In this issue of the BJGP, Kernick et al 6 report on a large cohort of patients presenting with new onset headache in primary care in the UK. They found that 70% were not given a diagnosis; 24% were diagnosed with either migraine, tension headache, or cluster headache; and 6% were diagnosed with secondary headache. This is similar to previous research. Primary care research, such as the Landmark 7 and Spectrum studies, 8 has shown that migraine is underdiagnosed and that tension-type headache and sinus headache are overdiagnosed.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.003 |
| 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 it