Increased A&E pressure and agency staff costs put foundation trusts further into red
Bibliographic record
Abstract
NHS foundation trusts in England became “less operationally resilient” in the last three months of 2014, with increased demand for services and their finances overstretched, especially in the acute care sector, the health sector regulator Monitor has reported. Foundation trusts failed for the third quarter in a row to meet targets set for waiting times in accident and emergency departments, for treatment for cancer, and for elective care, said the quarterly update on performance.1 It showed that the trusts saw 2.7 million people through emergency departments between October and December 2014, the same as in the previous quarter but 8% higher than in the same period last year. Subsequently, hospitals admitted 570 000 for further treatment, 40 000 more patients than in the same three months in 2013, said the report. The sector failed to meet the emergency department target for 95% …
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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) | 0.000 | 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) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".