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Record W4410247267 · doi:10.5376/ijms.2024.14.0039

Integrated Approaches to Restore Ecosystem Functions in Degraded Coral Reefs

2024· article· en· W4410247267 on OpenAlexvenueno aff
Xianming Li, Fei Zhao

Bibliographic record

VenueInternational Journal of Marine Science · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCoral reefResilience of coral reefsCoral reef organizationsAquaculture of coralReefEcosystemCoralCoral reef protectionEnvironmental scienceEnvironmental issues with coral reefsEcologyFisheryOceanographyGeologyBiology

Abstract

fetched live from OpenAlex

Coral reefs provide habitats for a vast array of marine life and play a crucial role in coastal protection, tourism, and fisheries. However, they are facing severe degradation due to multiple stressors such as climate change, overfishing, ocean acidification, and pollution. This study reviews the research progress on biological and technological interventions, including coral gardening, assisted evolution, 3D-printed artificial reefs, and genetic editing. It further explores the synergistic effects of these approaches across ecological, social, and governance dimensions. By analyzing successful cases and lessons from failures, the study proposes strategies integrating marine protected areas, habitat connectivity restoration, and community participation to enhance the resilience and recovery potential of coral reefs. The aim is to provide theoretical foundations and practical strategies for the conservation and restoration of coral reef ecosystems, contributing to global sustainable marine ecology.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.064
GPT teacher head0.256
Teacher spread0.192 · 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 teacher head, 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
Published2024
Admission routes1
Has abstractyes

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