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Record W2383402067

Characteristics of Sediment Yield and Supplying Pattern of the Laohahe Drainage Basin in Liaoning Province

2010· article· en· W2383402067 on OpenAlexaff
Yao Yu-zeng

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Changes in China
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsSedimentDrainage basinErosionHydrology (agriculture)Vegetation (pathology)Structural basinDrainageGeologyLithologySedimentary budgetLand useEnvironmental scienceSediment transportGeomorphologyGeographyGeochemistryGeotechnical engineeringEcology
DOInot available

Abstract

fetched live from OpenAlex

Based on the research on soil erosion of the Laohahe Drainage Basin in Liaoning Province, the spatial distribution of sediment delivery ratio of each morphological unit is determined by calculating sediment travel time, thus the final sediment yield is acquired. The result indicates that Laoguandi, Haladaokou, Shaoguoyingzi, etc in the northern part and both sides of the rivers in the middle and southern parts are the major sources of sediment yield. The mathematical model of sediment-supplying is established by choosing slope, vegetation coverage, land-use types, soil erodability, distance to the rivers and lithology of basement rocks as influencing factors, which reveals that the sediment yield is intimately related to slope, distance to rivers, land-use types and vegetation coverage. Thus, changing land-use types and/or increasing vegetation coverage is the key measure for disaster sediment. The result is helpful to the management of land-use and prevention of disaster sediment in the Laohahe Drainage Basin in the future.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.008
GPT teacher head0.202
Teacher spread0.195 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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