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Record W4220808495 · doi:10.5194/egusphere-egu22-10802

Changjiang sediment discharge to the East China Sea at the time scale of months to years

2022· preprint· en· W4220808495 on OpenAlexaff
Jinlong Wang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsKwantlen Polytechnic University
Fundersnot available
KeywordsEstuaryChemistryInternal medicineBiologyEcology

Abstract

fetched live from OpenAlex

The riverine derived particles play significant roles in sedimentological and geomorphological processes as well as biogeochemical cycles in estuaries. We collected a suite of water and sediment samples from the Changjiang (Yangtze) Estuary and adjacent East China Sea during to observe variations in the particulate 234Th, 7Be, 210Pb, and 137Cs activities as well as in particle transport, deposition, and resuspension. In the Changjiang Estuary, sedimentary particles in the North Passage experienced net deposition during neap tides whereas those in more seaward areas of the North Passage exhibited net resuspension during spring tides. based on a two-dimensional model of 7Be, 234Th, and 210Pb. Using 7Be/210Pbex and 137Cs/210Pbex activity ratios as tracers, we deduced that most of particles in the North Passage were not derived from the direct deposition of Changjiang input particles but were transported there from sediment deposited offshore. These riverine particles would undergo 3-6 years multiple cycles of deposition-resuspension-transport-deposition-resuspension before eventually buried in the shelf or export from inner shelf. The 7Be/210Pbex ratio indicates a southward transport pathway in spring and northeastward transport pathway in summer. Besides, 210Pb budget in the inner shelf of the ECS show that a small fraction (at most 14% of annual Changjiang sediment discharge in 2011) of particles could be transported offshore. The ratio of the mobile mud inventory of 234Thex/production in the overlying water column of > 2.5 in south inshore indicates that the sediment focusing resulted in the increased mass flux.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.206

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.006
GPT teacher head0.202
Teacher spread0.196 · 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
Published2022
Admission routes1
Has abstractyes

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