Evolution Amid Transition
Bibliographic record
Abstract
RecommendationsA s scientists and engineers, surely we are all comfortable with the classical concept of evolution?In fact, if we reach for our undergraduate texts, or perhaps our favorite online search engine, we can remind ourselves that "evolution...is the process by which species adapt over time in response to their changing environment."As a community of invested readers, authors, reviewers, and indeed editors, we can all agree that the global environment in which we live is visibly changing and prompting us, as communities, to make changes...and evolve!A recent message in our Editorial pages from Paul Anastas, the Chair of our Editorial Advisory Board (EAB), announced the dawning of a period of directed evolution for our journal.Over the next 6 months, we hope that you, as the constituents of our journal, will join us on a journey that will ensure our journal continues to support the needs of the global research community that we serve.At the top of his message, Paul recognized, and celebrated, the rock-solid foundations that are synonymous with strong leadership and excellence, and we now share with our community an update of our Executive Team who will support Peter Licence, the incoming Editor-in-Chief.We are thrilled to confirm that Professor Bala Subramaniam, University of Kansas, will continue his service as Executive Editor, and we are excited to welcome our newest Executive Editor, Professor Audrey Moores, McGill University, who has been part of our Editorial team for over six years.Bala will continue to provide oversight of targeted Virtual Special Issues and Perspectives Collections, while Audrey will help us to build on our program of community outreach and engagement to drive the promotion and visibility of the many outstanding research articles published in our journal.Together, the Executive Team will define an impact agenda that will embrace every aspect of diversity within our research community to ensure that we are "fit to play" and continue to provide thought leadership and advocacy at this critical time.To respond to rapidly changing socio-economic and technical challenges associated with delivery of the UN Sustainable Development Goals (SDGs), we recognize that the scope and direction of our journal has, and will, continue to evolve.Our journal will commission horizon-spanning collections from topical and impactful research communities.To underpin this exciting endeavor, we welcome Professor Kevin Leonard (University of Kansas) and Professor Graham Newton (University of Nottingham) as Topic Editors, a new role that empowers them to identify nascent hotspots that focus on societal needs and delivery of the United Nations Sustainable Development Goals (SDGs).As an Executive Team, we offer a warm welcome to our Topic Editors and
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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; 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".