Bibliographic record
Abstract
This special issue is based on papers originating from the sixth University Malaysia Terengganu Annual Seminar on Sustainability Science and Management: Ecosystem sustainability & health of threatened marine environments (ESHTME), which was organized by University Malaysia Terengganu (UMT) and the Aquatic Ecosystem Health and Management Society (AEHMS), Canada. The conference was sponsored by the Malaysian Ministry of Higher Education, and was held in May of 2007. Eighty-four presentations were made at the conference in both oral and poster formats. The program consisted of several invited and contributed presentations and dealt with such topics as oceanography, ecotoxicology and biodiversity. From these presentations, twenty-six manuscripts were submitted to the Journal for publication.All papers were subjected to a meticulous peer review process, as per the guidelines of the Journal; those that were accepted after the process are included in this ESHTME special issue. These manuscripts present a variety of topics ranging from sediments, physical and chemical oceanography, diatoms, biomarkers, mangroves, nuclear and isotopic techniques, hypoxia to the status of the Arabian Gulf ecosystem.Sincere thanks are due to Prof. Dr. Sulaiman Md Yassin, the former Vice Chancellor of UMT. We would like to thank the organizers and members of the various committees responsible, for making excellent arrangements for the convening of the conference. Thanks are also due to Fatimah Yusoff and Nagaraj Gopinath for their work on the Editorial Committee. Thanks are also due to the AEHMS publication committee for organizing the special issue, consisting of an interesting compendium of papers focusing on the Malaysian environment, about which not much is known. This is a welcome addition to our previous issue and the understanding of the aquatic ecosystems of Malaysia (Munawar et al., 2006). Finally we would like to thank the contributors, as well as the AEHMS secretariat: Lisa Elder, Jennifer Lorimer, and Susan Blunt for their hard work towards the production and publication of this special issue.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.536 | 0.521 |
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".