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Record W2783307174 · doi:10.1155/2018/9458410

Integrative Analysis of Surface Runoff and Macropore Flow for Slopes under Rainfall Conditions

2018· article· en· W2783307174 on OpenAlexafffund
Yun Que, Peiyuan Lin, Denghui Lin

Bibliographic record

VenueMathematical Problems in Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsMacroporeSurface runoffInfiltration (HVAC)Rainwater harvestingEnvironmental scienceSoil scienceHydrology (agriculture)Soil waterGeotechnical engineeringGeologyMaterials science

Abstract

fetched live from OpenAlex

Estimating runoff and infiltration in slopes is essential to predict flooding and landslide triggering. An approach jointly using a dual-permeability model and a kinematic wave model was proposed for integrative analyses of infiltration and surface runoff of rainwater for slopes with macropores in soils subjected to rainfalls. Laboratory tests were conducted to evaluate the performance of the proposed approach. Analyses showed that the presence of macropores greatly facilitates rainwater movement in the slope and the maximum depth of wetting front could be one order of magnitude larger than in cases without macropores. The influence of rainfall intensity, initial pore water pressure, coefficient of permeability of soil matrix, and slope angle was also examined.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.234
Teacher spread0.224 · 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 designSimulation or modeling
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

Citations11
Published2018
Admission routes2
Has abstractyes

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