Bibliographic record
Abstract
The future NHS: time for another change?How I agree with Roger Jones' insightful editorial.1 The NHS has experienced an artificial (but nonetheless increasing) divide between primary and secondary care for nearly a quarter of a century now.A parlance has evolved which incorporates concepts such as 'spend' 'provider' and 'activity'.It is regrettable that a whole generation of young medical and nursing staff don't know any different.Prior to leaving general practice a year ago I crossed the primary/secondary care divide for 1 day a week working as a GP with special interest in acute medicine.It was soon apparent that not only did staff in emergency departments speak negatively about 'the GP' or 'the community' but neither had they the slightest idea what went on outside their establishment.Surprisingly perhaps the converse was also true: hospital practice has changed out of all proportion since many of us were juniors.I still believe that being a GP is a wonderful career and things can only go upwards.However it is no coincidence that the most common question I was asked by junior hospital doctor colleagues and those that I trained was how to become a GPwSI in acute medicine.
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 | 0.016 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.021 |
| Scholarly communication | 0.019 | 0.033 |
| Open science | 0.006 | 0.016 |
| Research integrity | 0.207 | 0.158 |
| Insufficient payload (model declined to judge) | 0.047 | 0.013 |
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".