NHS choir’s number one hit puts health service in media spotlight over Christmas
Bibliographic record
Abstract
“I’m sure more improbable things have happened, but I can’t think of any,” said Eddie Chaloner, a member of the Lewisham & Greenwich NHS Choir, which hit the top of the UK singles chart this Christmas with the song “A Bridge Over You” (https://www.youtube.com/watch?v=T8qHXlShfUQ). The song clinched the number one slot from Justin Bieber on Christmas Day, outselling the Canadian singer’s song “Love Yourself” by 30 000 copies (127 000 versus 97 000). In the first chart of 2016 the song had dropped to number 29. Chaloner, a consultant vascular surgeon at University Hospital Lewisham, said that Bieber was “very helpful” when he tweeted his 72 million followers: “I’m hearing this UK Christmas race is close . . . but the NHS Choir single is for charity.” The choir, which includes all types of NHS staff, was …
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.298 | 0.076 |
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".