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Record W2126623208 · doi:10.1657/1938-4246-46.2.344

Distinct Fluvial Patterns of a Headwater Stream Network Underlain by Discontinuous Permafrost

2014· article· en· W2126623208 on OpenAlexaboutno aff
John T. Crawford, Emily H. Stanley

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
FundersU.S. Geological Survey
KeywordsPermafrostRiparian zoneSnowmeltGeologyDrainage densityFluvialHydrology (agriculture)STREAMSChannel (broadcasting)Drainage basinSnowPhysical geographyGeomorphologyStructural basinEcologyGeographyOceanographyGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract Hydrology, permafrost, and vegetation will likely respond to warming of northern latitudes with concurrent shifts in channel form and network pattern. At present, data on channel structure and networks in most northern regions are sparse, thus restricting any comprehensive understanding of channel processes or predictions of change in response to warming. We conducted a survey in 2011 of stream hydraulic geometry and network pattern in an upland headwater catchment of the Yukon River basin that is underlain by discontinuous permafrost. We found atypical hydraulic geometry exponents for depth and velocity but not for width and slope. We also found the study catchment to have unusually low drainage density and bifurcation ratios. Our data support the hypothesis that snow and channel ice decrease geomorphic effectiveness during snowmelt, which ultimately constrains channel and network development. Additionally, qualitative data support the hypothesis that dense riparian vegetation promotes bank stabilization and leads to nearly vertical channel walls in small streams, thus leading to anomalous hydraulic geometry. Simple metrics such as the drainage density and hydraulic geometry relationships may prove to be useful metrics of boreal and subarctic warming and permafrost thaw, and this study may serve as an important baseline to evaluate future changes.

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)0.001
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 score0.017
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0050.000

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 head0.039
GPT teacher head0.289
Teacher spread0.250 · 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

Citations16
Published2014
Admission routes1
Has abstractyes

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