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Record W1965562589 · doi:10.1115/imece2009-10607

Surface Runoff and Its Erosion Energy in a Partially Continuous System: An Ecological Hydraulic Model

2009· article· en· W1965562589 on OpenAlexaff
Huayong Zhang, Liming Dai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Agricultural Sciences
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsSurface runoffEnvironmental scienceEcosystemErosionDissipationHydrology (agriculture)Surface waterEcologyGeologyEnvironmental engineeringGeotechnical engineeringPhysicsGeomorphologyBiology

Abstract

fetched live from OpenAlex

Plant community and ground surface form a partially continuous ecosystem in conveying surface runoff and its erosion energy. It is one of the mechanisms for maintaining the stable development of a partially continuous ecosystem that the plant community and ground surface dissipate the erosion energy produced by surface runoff so as to control the soil erosion process of the ecosystem. Based on the energy fundamentals of hydraulics and by idealizing the structure of plant community, we obtain an ecological hydraulic model in this paper through a series of mathematical deductions, which includes three equations: (1) the equation on approaching energy balance of surface runoff moving across plant community and ground surface; (2) the equation on the process of dissipating energy of surface runoff by plant community and ground surface in an ecosystem; (3) the equation on the relationship among the pattern of plant community, ground surface and energy dissipation of surface runoff. Theoretically, the ecological hydraulic model can be used to calculate the dynamical process of energy dissipation of surface runoff by plant community and ground surface in a partially continuous ecosystem and to discuss the optimization of plant community pattern in a given section of the ecosystem.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.195
Teacher spread0.185 · 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

Citations6
Published2009
Admission routes1
Has abstractyes

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