Bibliographic record
Abstract
Jane Maher & Gina Radford speak to Gemma Westcott, Commissioning Editor Jane Maher has been Macmillan's Chief Medical Officer since 1999 and now shares the role as Joint Chief Medical Officer with general practitioner Rosie Loftus, reflecting the growing need for specialists and generalists to work more effectively together. She has been an National Health Service (NHS) improvement clinical leader for over 10 years and is a Consultant Clinical Oncologist at Mount Vernon Cancer Centre and Hillingdon Hospital where she has worked for more than 20 years, during which she helped develop nonsurgical oncology services in five district general hospitals. She is a senior Clinical Lecturer at University College London and Visiting Professor in Cancer and Supportive Care at the Centre for Complexity Management at the University of Hertfordshire. Jane chaired the Maher Committee for the Department of Health in 1995, led the UK National Audit of Late Effects Pelvic Radiotherapy for the Royal College of Radiologists (RCR) in 2000 and, most recently, chaired the National Cancer Survivorship Initiative Consequences of Treatment work stream. She co-founded one of the first Cancer Support and Information services in the UK, winning the Nye Bevan award in 1992 and there are now more than 60 units based on this model. She is a member of the Older People and Cancer Clinical Advisory Group. She has written more than 100 published articles and is a UK representative for cancer survivorship in Europe and advises on cancer survivorship programs in Denmark and Canada. Gina Radford is Deputy Chief Medical Officer for England, a post she took up in January 2015. Prior to that, she has held a number of roles in public health, at local and regional level. Most recently she was Centre Director for Anglia and Essex for Public Health England, and as a part of that role helped lead nationally on the public health response to Ebola. She was until very recently Chair of one of the NICE public health advisory committees. She has previously worked on a number of national projects, including leading the Department of Health's response to the Shipman Enquiry, undertaking a review of specialist public health for CMO Scotland, chairing a national short life working group looking at the issue of making difficult decisions in NHS Scotland, and undertaking the evaluation of the first pilot (regional bowel cancer detection pilot) for the Be Clear on Cancer National Awareness and Early Diagnosis campaign, on behalf of the Department of Health and Cancer Research UK. Outside work, Gina is a Licensed Lay Minister in the Church of England, and is training to be ordained. She enjoys riding, walking the somewhat aging dog, reading and is the village duck warden!
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".