Review of the evidence for Oceans and Human Health relationships in Europe: A systematic map
Bibliographic record
Abstract
Objectives: In this systematic map we aim to build on recent efforts to enhance OHH in Europe by setting a baseline of existing evidence, asking: What links have been researched between marine environments and the positive and negative impacts to human health and wellbeing? Methods: We searched eight bibliographic databases and queried 57 organizations identified through stakeholder consultation. Results include primary research and systematic reviews which were screened double blind against pre-defined inclusion criteria as per a published protocol. Studies were limited to Europe, US, Australia, New Zealand and Canada. Data was extracted according to a stakeholder-defined code book. A narrative synthesis explores the current evidence for relationships between marine exposures and human health outcomes, trends in knowledge gaps and change over time in the OHH research landscape. The resulting database is available on the website of the Seas, Oceans and Public Health in Europe website (https://sophie2020.eu/
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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 | 0.029 | 0.107 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.040 | 0.046 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".