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Record W4411888179 · doi:10.5670/oceanog.2025.315

Scientific Research and Marine Protected Area Monitoring Using a Deep-Sea Observatory: The Endeavour Hydrothermal Vents

2025· article· en· W4411888179 on OpenAlexafffund
S. F. Mihaly, Fabio De Leo, Ella Minicola, Lanfranco Muzi, M. Heesemann, Kate Moran, Jesse Hutchinson

Bibliographic record

VenueOceanography · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsOcean Networks Canada Society
FundersGovernment of Canada
KeywordsHydrothermal ventOceanographyObservatoryHydrothermal circulationGeologyDeep seaEnvironmental sciencePaleontology

Abstract

fetched live from OpenAlex

Designating marine protected areas (MPAs) is an increasingly utilized policy instrument for preserving marine ecosystems and biological diversity while also allowing for sustainable use. However, designation is only the first step and cannot be successful without monitoring mechanisms to drive an effective and adaptive management plan. This article discusses the use of the NEPTUNE real-time seafloor observatory—originally designed to understand the complex interdisciplinary nature of the Endeavour mid-ocean ridge spreading center—as a tool to inform MPA management. We describe the ways in which geophysical and geological forces control biological habitat and water column biogeochemistry, and highlight research enabled by the observatory that increased our understanding of Endeavour’s hydrothermal vent ecology and these dynamic processes. Endeavour is naturally undergoing change, so an understanding of the multidisciplinary mechanisms and factors controlling its environment provides key management information.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.075
GPT teacher head0.306
Teacher spread0.230 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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