MétaCan
Menu
Back to cohort
Record W2150631748 · doi:10.1002/eco.272

Slope effects on the spatial variations in duff moisture

2011· article· en· W2150631748 on OpenAlexaff
L. D. Raaflaub, Caterina Valeo, Edward A. Johnson

Bibliographic record

VenueEcohydrology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTransectMoistureSpatial variabilityEnvironmental scienceWater contentSoil scienceInterceptionHydrology (agriculture)GeologyEcologyGeographyGeotechnical engineeringMeteorologyMathematics

Abstract

fetched live from OpenAlex

ABSTRACT Investigations were made on the influence of slope on the spatial variations in duff moisture, the decomposing organic matter of the forest floor. Relationships between duff and soil moisture along hillslopes were identified from field measurements over various moisture conditions. Results indicated that duff moisture is not related to soil moisture, nor is it controlled by a hydraulic gradient. The spatial pattern of duff moisture over a 2 week period was established along two 2 m by 60 m hillslope transects that were sampled every 3 m. Because of interception, tree proximity was found to be the primary factor that significantly influenced the spatial variation in duff moisture. As the duff dried, the influence of tree proximity decreased. The distance from the top of the hillslope was not found to be an important factor in duff moisture variability. The spatial variation in duff moisture is more prominent during periods of wetness because of the exponential nature of the duff drying curve. Copyright © 2011 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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.172
Teacher spread0.166 · 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

Citations3
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueEcohydrologySame topicPlant Water Relations and Carbon DynamicsFrench-language works237,207