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Record W2888339984 · doi:10.1080/02626667.2018.1511905

Thresholds of land cover to control runoff and soil loss

2018· article· en· W2888339984 on OpenAlexaff
Masoud Eshghizadeh, Ali Talebi, Mohammad Taghi Dastorani

Bibliographic record

VenueHydrological Sciences Journal · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil erosion and sediment transport
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSurface runoffSoil lossEnvironmental scienceCover (algebra)Land coverHydrology (agriculture)Land useAgroforestryGeologyGeotechnical engineeringEngineeringEcologyCivil engineering

Abstract

fetched live from OpenAlex

This research focused on the determination of land cover thresholds that have a significant impact on runoff generation and soil loss at the pedon scale. For this purpose, six erosion micro-plots were set up on grassland and shrubland types of rangeland in the northeast of Iran, and the amounts of vegetation cover, litter, runoff and soil loss on them were measured. A factorial statistical analysis was carried out on the completely randomized design using land cover and rainfall factors. The results show that the effect of rainfall on soil loss and runoff was greater than that of land cover. Also, the effect of land cover on soil loss was greater than that on runoff generation. Furthermore, two specific thresholds were identified: the first was from 10 to 30% of landcover and the second from 50 to 70%.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.021
GPT teacher head0.239
Teacher spread0.218 · 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

Citations19
Published2018
Admission routes1
Has abstractyes

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