MétaCan
Menu
Back to cohort

In Situ Size Distribution of Suspended Particles in the Fraser River

2000· article· en· W4231384962 on OpenAlexafffundabout
Bommanna G. Krishnappan

Bibliographic record

VenueJournal of Hydraulic Engineering · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsEnvironment and Climate Change Canada
FundersGovernment of CanadaNational Water Research Institute
KeywordsFlocculationEstuarySedimentEnvironmental scienceOutfallEffluentHydrology (agriculture)Suspended solidsParticle-size distributionGeologyOceanographyEnvironmental engineeringParticle sizeWastewaterGeomorphologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Size distributions of suspended sediment particles under low flow conditions in the Fraser River were measured using a submersible laser instrument. By comparing the in situ size distribution measured using this instrument with the size distribution of primary particles (measured by collecting sediment samples and analyzing them for size distribution after dispersing the particles by ultrasonic vibration), it was concluded that suspended sediment particles in the Fraser River downstream of pulp mill effluent outfalls are transported as agglomerations of particles (flocs) rather than as individual particles. Flocculation of river sediments in estuaries has been investigated in earlier studies, which show that saltwater intrusion contributes to the flocculation mechanism. Freshwater flocculation, such as the one observed in the present study, also has been reported in the literature, and it is attributed to the presence of organic materials and other contaminants from industrial and sewage treatment plant effluents. This paper describes the details of the submersible laser instrument and its use in the Fraser River, British Columbia, Canada.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.200
Teacher spread0.194 · 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

Citations28
Published2000
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Hydraulic EngineeringSame topicGroundwater flow and contamination studiesFrench-language works237,207