Bibliographic record
Abstract
Oceanography and Marine Biology: An Annual Review remains one of the most cited sources in marine science and oceanography. The ever-increasing interest in work in oceanography and marine biology and its relevance to global environmental issues, especially global climate change and its impacts, creates a demand for authoritative refereed reviews summarizing and synthesizing the results of both historical and recent research. This Volume celebrates 60 years of OMBAR, over which time it has been an essential reference for research workers and students in all fields of marine science. The peer-reviewed contributions in Volume 60 are available to read Open Access via this webpage and on OAPEN. If you are interested in submitting a review for consideration for publication in OMBAR, please email the Editor-in-Chief, Stephen Hawkins (S.J.Hawkins@soton.ac.uk) for Volume 61. For Volume 62 onwards, please email the new co-Editors in Chief, Dr Peter Todd (dbspat@nus.edu.sg) and Dr Bayden Russell (brussell@hku.hk). Volume 60 features an editorial on the UN Decade of Ocean Science and goes on to consider such diverse topics as Cenozoic tropical marine biodiversity, blue carbon ecosystems in Sri Lanka, marine litter and microplastics in the Western Indian Ocean, and the ecology and conservation status of the family Syngnathidae in southern and western Africa. This volume also contains a retrospective Prologue on the evolution of OMBAR and pays tribute to one of its early Editors in Chief, Margaret Barnes, by providing an update on her review in OMBAR of the stalked barnacle Pollicipes. Supplementary online videos as well as additional Tables and Appendices are available on the Support Tab of the book's Routledge webpage. An international Editorial Board ensures global relevance and expert peer review, with editors from Australia, Canada, Hong Kong, Ireland, Singapore and the UK. The series volumes find a place in the libraries of not only marine laboratories and oceanographic institutes, but also universities worldwide.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.947 | 0.947 |
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; the direct Gemma label and the distilled Codex classifier 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".