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Record W1560901933 · doi:10.7202/1018788ar

Relationships among man, environment and sediment transport

2013· article· en· W1560901933 on OpenAlexfundno aff
Gil Mahé, Hafzullah Aksoy, Yao Télesphore Brou, Mohamed Meddi, Éric Roose

Bibliographic record

VenueRevue des sciences de l eau · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil erosion and sediment transport
Canadian institutionsnot available
FundersTürkiye Bilimsel ve Teknolojik Araştırma KurumuAgence Universitaire de la FrancophonieNational Research Foundation
KeywordsSediment transportSedimentMediterranean climateScale (ratio)AgricultureLand degradationClimate changeLand useSurface runoffEnvironmental scienceAridWater resourcesEnvironmental resource managementGeographyHydrology (agriculture)EcologyGeologyOceanographyEngineeringCivil engineering

Abstract

fetched live from OpenAlex

In the Mediterranean the environment is under pressure from agricultural and urban development, changes in agricultural practices and international markets, and climate change. Moreover, many studies show a steady increase in the agro-pastoral pressure and land degradation and their impacts on water resources and soil, and ultimately the lives of local people. But few studies address these issues across the inclusive scale of large river basins. The conference held at Tipaza in Algeria, from which come several papers published in the Journal of Water Science in 2013, was intended to reflect on the topics, methods and tools available to study the relationships among humans, the environment and sediment transport at this large scale, with the result expected to improve the potential for dialogue between researchers and developers who make decisions for regional macro surfaces. The topics discussed at the conference that appear in the articles published here concern the factors responsible for the variability of sediment transport: climate change and anthropogenic changes, such as agricultural activity and water projects; relationships between land-cover/land-use, rainfall-runoff processes and sediment transport; modeling of sediment transport; and the interest of a multi-scale approach, predominantly a spatial one, for addressing the geographical realities of large basins and scale transfer issues, particularly in Mediterranean and semi-arid areas.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.095
GPT teacher head0.231
Teacher spread0.136 · 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 teacher head, not a consensus.

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

Citations5
Published2013
Admission routes1
Has abstractyes

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