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Transverse Mixing in an Unregulated Northern River

2011· article· en· W1965391120 on OpenAlex
Wenming Zhang, David Z. Zhu

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Hydraulic Engineering · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTransverse planeMixing (physics)Dimensionless quantityHydrology (agriculture)Environmental scienceMechanicsGeologyGeotechnical engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

Transverse mixing in an unregulated northern river in Canada was studied in different discharge conditions with and without ice cover. The distribution of cumulative discharge was constructed on the basis of river cross-sectional shapes, and a modified streamtube method was proposed to describe transverse mixing. The modified method only uses raw field data to calibrate the modeled concentration profiles and thus, can produce a reliable mixing coefficient even with relatively low-quality field data. The effects of river discharge and ice cover on the transverse mixing coefficient were examined in a fixed study reach. It was found that the transverse mixing coefficient increased approximately linearly with river discharge (from 84 to 960 m3/s). The dimensionless transverse mixing coefficient, scaled with river shear velocity and river depth, appeared unaffected (within 14%) by the river discharge in both open-water and ice-covered conditions, and its value was 21% smaller in the ice-covered condition than in the open-water condition.

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.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.123
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.013
GPT teacher head0.181
Teacher spread0.168 · 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