Perspectives on Documenting Methods to Create Ocean Best Practices
Bibliographic record
Abstract
This perspective outlines how authors of ocean methods, guides, and standards can harmonize their work across the scientific community. We reflect on how documentation practices can be linked to modern information technologies to improve discoverability, interlinkages, and thus the evolution of distributed methods into common best practices within the ocean community. To show how our perspectives can be turned into action, we link them to guidance on using the IOC-UNESCO Ocean Best Practice System to support increased collaboration and reproducibility during and beyond the UN Decade of Ocean Sciences for Sustainable Development.
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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 | 0.214 | 0.177 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.012 | 0.072 |
| Scholarly communication | 0.048 | 0.058 |
| Open science | 0.008 | 0.027 |
| Research integrity | 0.018 | 0.023 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".