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BED MATERIAL TRANSPORT AND THE MORPHOLOGY OF ALLUVIAL RIVER CHANNELS

2006· article· en· W2101354433 on OpenAlexaff
Michael Church

Bibliographic record

VenueAnnual Review of Earth and Planetary Sciences · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAlluviumSedimentSedimentationSediment transportChannel (broadcasting)GeologyRiver morphologyAggradationAlluvial fanGeomorphologyHydrology (agriculture)FluvialGeotechnical engineeringStructural basinEngineering

Abstract

fetched live from OpenAlex

The morphology of an alluvial river channel is the consequence of sediment transport and sedimentation in the river. Morphological style is determined chiefly by the caliber and quantity of sediment delivered to the channel, although modulated by channel scale. Yet the relations between sediment transport and river morphology have received only limited, qualitative attention. In this review, the problem is studied by defining sediment transport regimes on the basis of the Shields number, a nondimensional measure of the capacity of the channel to move sediment of a given caliber. The problem is also approached from an inverse perspective by which the quantity and character of sediment deposits are used to infer details about the variation of sediment transport and sedimentation along a channel. Coupling the two approaches establishes a basis to gain new insights into the origins of alluvial channel morphology.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
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 head0.199
Teacher spread0.193 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations809
Published2006
Admission routes1
Has abstractyes

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