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Status of the World's Soils

2024· article· en· W4402249831 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnual Review of Environment and Resources · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsEnvironmental scienceSoil waterEcosystem servicesSoil functionsBiodiversityAgricultureSoil biodiversityEnvironmental protectionEnvironmental planningBusinessEnvironmental resource managementNatural resource economicsEcosystemSoil organic matterGeographyEcologySoil science

Abstract

fetched live from OpenAlex

Healthy soils contribute to a wide range of ecosystem services and virtually all of the UN Sustainable Development Goals, but most of the world's soil resources are in only fair, poor, or very poor condition, and conditions are getting worse in more cases than they are improving. A total of 33% of all soils are moderately to highly degraded as a result of erosion, loss of organic matter, poor nutrient balance, salinization and alkalinization, contamination, acidification, loss of biodiversity, sealing, compaction, and poor water status. Best management practices are available to limit or mitigate threats to soil health, and many of them mitigate multiple soil threats. In many regions of the world, policies or initiatives to protect or enhance the status of soils are in place, and they need to be strengthened and enforced. The Food and Agriculture Organisation will publish its second comprehensive assessment of the status of the world's soils in 2025, and this review provides an interim update on world soil status and offers an accessible overview of the topic.

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.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.254
Teacher spread0.245 · 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