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Record W2806336697 · doi:10.1029/2017jc013650

Analysis of Hypoxia and Sensitivity to Nutrient Pollution in Salish Sea

2018· article· en· W2806336697 on OpenAlexaff
Tarang Khangaonkar, Adi Nugraha, Wenwei Xu, Wen Long, Laura Bianucci, Anise Ahmed, Teizeen Mohamedali, Greg Pelletier

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsFisheries and Oceans Canada
FundersUniversity of Washington
KeywordsPhotic zoneEnvironmental scienceHypoxia (environmental)NutrientOceanographyBiogeochemical cyclePhytoplanktonWater columnAlgal bloomWater qualityEutrophicationHydrology (agriculture)EcologyGeologyBiologyChemistryOxygen

Abstract

fetched live from OpenAlex

Abstract Increasing levels of nutrients, persistent hypoxia, harmful algal blooms, and increased frequency of fish kills are degrading the ecological health of the Salish Sea. An improved version of a diagnostic hydrodynamic and biogeochemical model (nutrients, phytoplankton, carbon, dissolved oxygen, and pH) of the Salish Sea has been developed with the ability to simulate characteristic circulation and water quality features. Sensitivity tests were conducted to assess the responsiveness of the system to land‐based (rivers and wastewater sources) nutrient loading. The influence of Fraser River on the magnitude of estuarine exchange with the Pacific Ocean and nearshore habitat was examined given that it contributes nearly half of the total freshwater discharged to the Salish Sea. A large region of hypoxia in Hood Canal that extends over 30–40 km during its peak was reproduced and attributed primarily to the existence of a two‐layer classic fjord‐type circulation and a nearly stagnant deep bottom layer that occupies nearly 60% of the water column. Nitrate mass in the euphotic zone from land‐based and oceanic sources is depleted to near‐zero limiting levels during summer. Under such conditions, the Salish Sea is responsive to changes in nutrient loads entering the euphotic zone directly. A hypothetical scenario involving the elimination of land‐based nutrient sources results in notable water‐quality improvement, featuring a reduction in algal biomass (≈5.4%), reduction in sediment oxygen demand (≈17.1%), and significant reduction in hypoxic area (≈39%) and exposure in area‐days to bottom layer hypoxia (≈62%) within the Salish Sea.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.021
Threshold uncertainty score0.232

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
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 head0.024
GPT teacher head0.299
Teacher spread0.274 · 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

Citations80
Published2018
Admission routes1
Has abstractyes

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