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Record W2036920273 · doi:10.1002/hyp.1396

Throughflow variability during snowmelt in a forested mountain catchment, coastal British Columbia, Canada

2004· article· en· W2036920273 on OpenAlexaffabout
Hyeon Jeong Kim, Roy C. Sidle, R. D. Moore, Robert O. Hudson

Bibliographic record

VenueHydrological Processes · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of British Columbia
FundersFu Foundation School of Engineering and Applied Science
KeywordsThroughflowSnowmeltOutflowHydrology (agriculture)GeologyStreamflowInterflowDrainage basinSnowGeomorphologyGroundwaterOceanographySoil scienceGeography

Abstract

fetched live from OpenAlex

Abstract This study documented the spatial and temporal variability of outflow from a forested hillslope segment during snowmelt at a small mountain catchment in south coastal British Columbia, Canada. A pit 5 m wide was established just upslope from the stream channel. Outflow from the organic horizon was intercepted and measured by a single trough, and outflow from the mineral horizons was measured separately for three adjacent sections. Throughflow exhibited non‐steady‐state behaviour involving shifting allocations of flow amongst different sections of the outflow pit, as well as threshold effects and hysteresis in the relationship between pit outflow and water table elevation. Most of the pit outflow originated from the mineral horizons, indicating that throughflow was the dominant pathway by which water was delivered to the stream channel. Direct precipitation and snowmelt onto near‐stream saturated areas can account for less than 20% of the total outflow from the hillslope segment. Throughflow from the mineral sections consistently peaked either at the same time as or earlier than stream flow from the 150‐ha catchment during diurnal snowmelt cycles, indicating that throughflow appears to respond rapidly enough to contribute to snowmelt‐induced peak stream flow. Pit outflow cannot be extrapolated reliably to the catchment scale on the basis of simple length‐ or area‐based ratios. Copyright © 2004 John Wiley & Sons, Ltd.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
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 head0.012
GPT teacher head0.196
Teacher spread0.184 · 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 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

Citations35
Published2004
Admission routes2
Has abstractyes

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