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Record W2021373812 · doi:10.1130/g33106.1

Lithologic and glacially conditioned controls on regional debris-flow sediment dynamics

2012· article· en· W2021373812 on OpenAlexaff
Francesco Brardinoni, Michael Church, Alessandro Simoni, Pierpaolo Macconi

Bibliographic record

VenueGeology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLithologyDebris flowArchaeologyHistoryHumanitiesLibrary scienceDebrisGeologyArtOceanographyComputer sciencePaleontology

Abstract

fetched live from OpenAlex

Debris flow is an efficient process of sediment transfer from
\nslope base to piedmont depositional fans in mountain drainage
\nbasins. To advance understanding of debris-flow sediment dynamics
\nat the regional scale, we analyze a historical (1998–2009) database
\nof debris flows from 77 basins of Alto Adige Province, northeastern
\nItaly. By combining information on event volumetric deposition,
\nhigh-resolution digital topography, and Quaternary sediment
\nmapping we are able to link debris-flow sediment flux to morphometry, lithologic variability, and sediment availability. We show that basin-wide specific sediment yield (SSY) scales as an inverse power function of basin area. This function is strongly controlled by the way rock type and abundance of Quaternary deposits affect the rate of downstream sediment recruitment. When sediment flux associated with each debris-flow event is subsumed across discrete spatial increments of the entire region, a complex sedimentary signature in the area-SSY space is apparent. That is, SSY increases downstream up to areas as large as 1 km2, and starts to decline beyond this scale, regardless of sediment availability. We propose that this area-SSY relation is characteristic of debris flow–dominated settings.

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 score0.039
Threshold uncertainty score0.999

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)0.0020.001

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 head0.215
Teacher spread0.207 · 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

Citations39
Published2012
Admission routes1
Has abstractyes

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