MétaCan
Menu
Back to cohort
Record W4410412272 · doi:10.1038/s44183-025-00119-4

Marine spatial planning and marine protected area planning are not the same and both are key for sustainability in a changing ocean

2025· review· en· W4410412272 on OpenAlex
Catarina Frazão Santos, Lisa M. Wedding, Tundi Agardy, Julie Reimer, Elena Gissi, Helena Calado

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenpj Ocean Sustainability · 2025
Typereview
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsFisheries and Oceans Canada
FundersHORIZON EUROPE European Research CouncilFundação para a Ciência e a TecnologiaEuropean Commission
KeywordsMarine spatial planningSustainabilityKey (lock)Marine protected areaEnvironmental resource managementEnvironmental planningOceanographyEnvironmental scienceGeographyGeologyComputer scienceEcology

Abstract

fetched live from OpenAlex

Marine spatial planning (MSP) and marine protected area (MPA) planning are two distinct area-based management processes that are often conflated. While engaging in MPA planning is crucially important for biodiversity conservation and localized sustainable use, it cannot bring the benefits that larger scale MSP can deliver. Confusing the two can lead not only to missed opportunities to support ocean sustainability, but also to inefficiencies and even conflict. Here, we clearly define and distinguish each approach, then discuss opportunities to optimise synergies, especially under rapidly changing climate. MSP can support conservation efforts by taking the broader context into account, while integrating conservation and MPA planning into MSP allows for the maintenance of ocean health-always a core goal of marine management.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.792
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.012
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.278
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it