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Record W4401649534 · doi:10.5376/ijms.2024.14.0020

Beneath the Storm: A Comparative Analysis of Natural and Anthropogenic Factors in Marine Biogeochemical Dynamics

2024· article· en· W4401649534 on OpenAlexvenueno aff
Haimei Wang

Bibliographic record

VenueInternational Journal of Marine Science · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine Biology and Ecology Research
Canadian institutionsnot available
Fundersnot available
KeywordsBiogeochemical cycleStormEnvironmental scienceNatural (archaeology)OceanographyEcologyGeographyGeologyBiology

Abstract

fetched live from OpenAlex

The paper titled "Biogeochemical dynamics in a marine storm demonstrates differences between natural and anthropogenic impacts," authored by Justin Tiano, Rob Witbaard, Theo Gerkema, and Karline Soetaert, from Wageningen Marine Research, Wageningen University and Research, Department of Estuarine and Delta Systems, Royal Netherlands Institute for Sea Research (NIOZ), was published in Scientific Reports on April 16, 2024. This study explores the impact of storms on marine biogeochemical dynamics, particularly focusing on the differences between natural and anthropogenic disturbances. By comparing the effects of natural storms and bottom trawling on seabed suspended particulate matter, the research found that turbidity induced by storms was significantly higher than recent trawling events. This study offers a new perspective on understanding how storms and human activities affect marine ecosystems.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.315
Teacher spread0.296 · 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.

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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