Bibliographic record
Abstract
CHOICE Highly Recommended, Sept 2022 \n \nOceanography 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 recent research. \n \nFor nearly 60 years, OMBAR has been an essential reference for research workers and students in all fields of marine science. This volume considers such diverse topics as the Great Barrier Reef Expedition of 1928-29, Mediterranean marine caves, macromedusae in eastern boundary currents, marine biodiversity in Korea, and development of a geo-ecological carbonate reef system model to predict responses of reefs to climate change. Volume 59 is available to read Open Access on the Taylor & Francis eBooks site (https://www.taylorfrancis.com/books//10.1201/9781003138846) \n \nAn international Editorial Board ensures global relevance and expert peer review, with editors from Australia, Canada, Hong Kong, Ireland, Singapore and the United Kingdom. The series volumes find a place in the libraries of not only marine laboratories and oceanographic institutes, but also universities worldwide. \n \nIf you are interested in submitting a review for consideration for publication in OMBAR, please email the Editor in Chief, Stephen Hawkins, at S.J.Hawkins@soton.ac.uk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.010 | 0.012 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.990 | 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; both teacher heads 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".