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Record W4413258942 · doi:10.5376/ijms.2025.15.0007

Biodiversity and Ecological Functions of Coral Reef Fish in Hainan Island and the South China Sea

2025· article· en· W4413258942 on OpenAlexvenueno aff
Haimei Wang, Guilin Wang

Bibliographic record

VenueInternational Journal of Marine Science · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCoral reefEnvironmental issues with coral reefsGeographyBiodiversityFisheryCoral reef protectionChinaReefEcologyCoral reef fishAquaculture of coralMarine biodiversityFish <Actinopterygii>Biology

Abstract

fetched live from OpenAlex

This study explored the role of coral fish in core ecological functions such as material cycling, algal regulation and habitat construction, focusing on the species diversity characteristics, population distribution patterns and ecological contributions of coral reef fish in Hainan Island and the South China Sea. Reef fish maintain the stability and resilience of coral reef systems through multiple pathways such as energy transfer, carbon sequestration, and clean symbiosis. The Hainan Island and the South China Sea region are facing a combination of pressures such as illegal fishing operations, climate change, land-based pollution and habitat fragmentation, resulting in the simplification of the biological community structure, functional degradation and the attenuation of ecological services. This study aims to assist in building a cross-regional Marine protected area network, implement eco-friendly fishery policies, strengthen basic scientific research and real-time monitoring systems, establish a multi-party collaborative management mechanism, provide scientific basis for the sustainable governance of regional coral reef ecosystems, and contribute to the coordinated optimization of ecological conservation and resource utilization.

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 score0.012
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.006
GPT teacher head0.211
Teacher spread0.206 · 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
Published2025
Admission routes1
Has abstractyes

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