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Record W2888240183 · doi:10.1029/2018jc014093

Variability of Suspended Particle Properties Using Optical Measurements Within the Columbia River Estuary

2018· article· en· W2888240183 on OpenAlexaff
Jing Tao, Paul S. Hill, Emmanuel Boss, Timothy G. Milligan

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans CanadaDalhousie University
FundersOffice of Naval ResearchU.S. Geological Survey
KeywordsEstuaryTurbidityFlocculationSalinityParticle sizeParticle-size distributionParticle (ecology)Environmental sciencePopulationOceanographyGeology

Abstract

fetched live from OpenAlex

Abstract Optical properties are used to understand the spatial and temporal variability of particle properties and distribution within the Columbia River Estuary, especially in the salinity transition zone and in the estuarine turbidity maximum region. Observations of optical properties in the Columbia River Estuary are consistent with the established model that the river water brings more organic, smaller particles into the estuary, where they flocculate and settle into the salt wedge seaward of the density front. Large tidal currents resuspend mineral‐rich, larger aggregates from the seabed, which accumulate at the density front. Optical proxies for particle size (beam attenuation exponent γ and backscattering exponent γ b b ) are compared to conventional measurements. The γ and γ b b are different to the expected trend with Sauter mean diameter D s of suspended particles from low‐ to medium‐salinity waters (LMW). D s increases in the LMW as does the γ derived from a WET Labs ac‐9, which indicates that the particle population dominating the ac‐9 is decreasing in size. The most likely explanation is that flocculation acting at LMW transfers mass preferentially from medium‐sized particles to large‐sized particles that are out of the size range to which the ac‐9 is most sensitive; γ b b shows no trend in the LMW. Since γ b b is a proxy of proportion of fine particles versus large flocs, the variation of γ b b may be insensitive to changes in the medium‐sized particles. The overall results demonstrate that γ b b is a reliable proxy for changes in particle size in a stratified environment.

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)0.005
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 score0.093
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
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 science0.0000.000
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 head0.122
GPT teacher head0.307
Teacher spread0.186 · 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

Citations22
Published2018
Admission routes1
Has abstractyes

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