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Record W1973906530 · doi:10.1130/g30861.1

Can we distinguish flood frequency and magnitude in the sedimentological record of rivers?

2010· article· en· W1973906530 on OpenAlexaboutno aff
Gregory H. Sambrook Smith, Jim Best, Philip J. Ashworth, Stuart N. Lane, Natalie O. Parker, I. Lunt, Robert E. Thomas, Christopher J. Simpson

Bibliographic record

VenueGeology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
FundersNatural Environment Research Council
KeywordsHistoryFlood mythArchaeologyArt history

Abstract

fetched live from OpenAlex

Consideration of the origin of alluvial deposits and their paleoenvironmental interpretation has traditionally involved two schools of thought: that they are either the result of processes that, on average, have acted uniformly through time, or that they are related to exceptional events that occur infrequently. Despite the long-running debate of gradualism versus catastrophism within the Earth Sciences, there are surprisingly few quantitative data to assess the magnitude of events that produce alluvial sedimentary successions. This paper reports on a unique ‘natural experiment’ where surface (digital elevation model, DEM) and subsurface (ground penetrating radar, GPR) data were taken immediately prior to, and after, a large (1-in-40 yr) flood event on the sandy, braided, South Saskatchewan River, Canada. Results show that although this high-magnitude flood reworked the entire braidplain, the scale of scour and style of deposition was similar to that associated with lower-magnitude, annual, floods. The absence of a distinct imprint of this large flood within the deposits is related to the fact that as river discharge rises, and begins to flow overbank, channel width increases at a much faster rate than flow depth, and thus the rate of increase in channel bed shear stress declines. Hence, rather than being a product of either frequent or rare events, alluvial deposits will likely be created by a range of different magnitude floods, but discriminating between these different scale events in the rock record may be extremely difficult.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.998

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.214
Teacher spread0.206 · 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.

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

Citations73
Published2010
Admission routes1
Has abstractyes

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