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Record W2767863034 · doi:10.1080/04353676.2017.1366830

Sediment loading of alpine debris-flow channels by snow avalanches, Canadian Rocky Mountains

2017· article· en· W2767863034 on OpenAlexafffundabout
Graham D. Woodhurst, Fes A. de Scally

Bibliographic record

VenueGeografiska Annaler Series A Physical Geography · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersUniversity of British ColumbiaParks Canada
KeywordsDeposition (geology)GeologyDebrisSedimentDebris flowHydrology (agriculture)GeomorphologySnowMeltwaterChannel (broadcasting)SnowmeltGeotechnical engineeringOceanography

Abstract

fetched live from OpenAlex

Measurements of sediment deposition by snow avalanches were carried out in five alpine debris-flow channels in the Canadian Rocky Mountains after five or six winters by employing on average 15–29 sampling polygons in each channel. Following the melting of the avalanche snow each summer, the sediment deposited inside each polygon was collected, weighed, and converted to a depth of deposition. The results show that deposition in the channels averages 0.09–0.38 cm a−1, with an overall average of 0.19 cm a−1 for the five channels. Most of this deposition is contributed by weak clastic rocks in the basins but the largest particles are derived from much stronger carbonate rocks. Taking into account the channel area over which the measurements were made and the basin area, the measured sediment depths are equivalent to 8.3–36.4 m3 a−1 of deposition per channel or 10.9–311.7 t km−2 a−1 basin sediment yield. For the five channels, the overall averages are 16.4 m3 a−1 and 95.8 t km−2 a−1, respectively. On average 8–38% of polygons in each channel had no sediment deposition after a winter, reflecting the high spatial variability of avalanche sediment deposition. Comparison of debris-flow volumes and return periods with the measured annual volumes of sediment deposition suggests that avalanches are by themselves incapable of loading these channels for debris flows, and other processes such as rockfall, creep and streamflow also play a role. The most important role of avalanches may be as a hillslope-channel coupling mechanism in the sediment cascade and to assist in debris-flow bulking on the fan.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.211
Teacher spread0.205 · 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

Citations1
Published2017
Admission routes3
Has abstractyes

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