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Record W2022129302 · doi:10.5194/bg-11-7061-2014

Biogeochemistry and ecosystems of continental margins in the western North Pacific Ocean and their interactions and responses to external forcing – an overview and synthesis

2014· article· en· W2022129302 on OpenAlexaff
Kon‐Kee Liu, Chang Keun Kang, Toru Kobari, Hongbin Liu, Christophe Rabouille, Katja Fennel

Bibliographic record

VenueBiogeosciences · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsDalhousie University
FundersMinistry of Science and Technology, TaiwanNational Science CouncilNational Science Foundation
KeywordsBiogeochemical cycleMarine ecosystemOceanographyBiogeochemistryEcosystemContinental shelfEnvironmental scienceClimate changeContinental marginGeologyEcologyBiology

Abstract

fetched live from OpenAlex

Abstract. In this special issue we examine the biogeochemical conditions and marine ecosystems in the major marginal seas of the western North Pacific Ocean, namely, the East China Sea, the Japan/East Sea to its north and the South China Sea to its south. They are all subject to strong climate forcing as well as anthropogenic impacts. On the one hand, continental margins in this region are bordered by the world's most densely populated coastal communities and receive tremendous amount of land-derived materials. On the other hand, the Kuroshio, the strong western boundary current of the North Pacific Ocean, which is modulated by climate oscillation, exerts strong influences over all three marginal seas. Because these continental margins sustain arguably some of the most productive marine ecosystems in the world, changes in these stressed ecosystems may threaten the livelihood of a large population of humans. This special issue reports the latest observations of the biogeochemical conditions and ecosystem functions in the three marginal seas. The studies exemplify the many faceted ecosystem functions and biogeochemical expressions, but they reveal only a few long-term trends mainly due to lack of sufficiently long records of well-designed observations. It is critical to develop and sustain time series observations in order to detect biogeochemical changes and ecosystem responses in continental margins and to attribute the causes for better management of the environment and resources in these marginal seas.

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 score0.058
Threshold uncertainty score0.993

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.021
GPT teacher head0.228
Teacher spread0.207 · 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

Citations23
Published2014
Admission routes1
Has abstractyes

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