Bibliographic record
Abstract
The Promise of the Health Sciences in the 21st Century here's a revolution taking place in the health sciences and it's forcing a different view of human health and healthcare in the 21st century.The roots of this revolution can be found in the rapid and convergent advances in fields of research as diverse as genetics, chemistry, population health and computational science.The increasingly multidisciplinary nature of health research also stems from the full engagement of healthcare "consumers" -patients, the public, healthcare providers and policy-makers -in the health research enterprise.Taken together, these changes have transformed the nature and focus of health research, simultaneously opening the doors to profound complexity, but also holding the promise of comprehensive systems solutions to seemingly intractable problems, whether it's the mysteries of the human body or our health system.These changes have also created a new imperative for healthcare.The health sciences revolution is pressuring governments and societies everywhere to rethink and re-engineer existing health institutions and research approaches.In this new universe, it is clear that science must inform the development of public policy.At the same time, public policy and the public interest will increasingly inform and guide the directions of research carried out with public funds.The recent creation of the Canadian Academies of Health Sciences is both timely and necessary; this organization will play a vital role as an advisor and partner, helping navigate the challenges and opportunities in the changing health sciences landscape.Changes in this landscape had their origins in the colossal advances in deciphering the cellular and molecular basis of life.Deriving the sequence of the human genome and the Canadian discovery of stem cells did more than just advance our understanding of the human body.Virtually overnight, it transformed biology and medicine from a descriptive science to an information science, right in the middle of the revolution occurring in the information and communication technologies.This revolution in genomics and its sister sciences is not the only scientific and technological revolution going on in the health sciences.Clinical and population epidemiology have had remarkable successes in teasing out the risk factors of disease.Most recently, the Interheart Study by Dr. Salim Yusuf at McMaster University, with his colleagues from around the world, identified dietary factors, exercise, obesity, excessive drinking and so on as risk factors for heart disease, diabetes and stroke.We no longer think of chronic diseases as the inevitable consequences of aging -they are all due to specific, attributable risk factors and they are not inevitable.Each of these achievements has set the stage for further
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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 | 0.012 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.038 | 0.043 |
| Insufficient payload (model declined to judge) | 0.032 | 0.018 |
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".