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Record W4304809609 · doi:10.1139/er-2021-0128

Does land use legacy matter for current soil functioning? A bibliometric study (2001–2020)

2022· article· en· W4304809609 on OpenAlexvenueno aff
Ninon Delcourt, Catherine Rébufa, Claude Périssol, Nathalie Dupuy

Bibliographic record

VenueEnvironmental Reviews · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil erosion and sediment transport
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeContext (archaeology)Psychological resilienceEnvironmental resource managementVulnerability (computing)Land useProxy (statistics)GeographyEnvironmental scienceEnvironmental planningNatural resource economicsEcologyPsychology

Abstract

fetched live from OpenAlex

This article applies the tools of bibliometric analyses to explore the evolution and strategic orientation of research focusing on the temporal dynamics of land use, which can be considered as an important proxy to assess soil vulnerability. With 1416 papers published in 417 different journals, the investigation showed a growing interest in the subject during the period ranging from 2001 to 2020. The main countries working on that topic are the USA, China, and certain countries of the European Union with a worldwide collaboration regarding coauthors. A cluster analysis of the keywords generated 6 main themes of research, each focusing on different issues and approaches, that is, greenhouse gas emissions, soil nutrients, climate change, erosion risk, human disturbances as well as resilience of soil functioning. Finally, it appears that the effect of land use legacy is poorly considered in the context of climate change, which could represent a future line of research.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.045
GPT teacher head0.260
Teacher spread0.214 · 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

Labeled directly by 2 models reading the full record.

Bibliometrics

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueEnvironmental ReviewsSame topicSoil erosion and sediment transportCategoryBibliometricsFrench-language works237,207