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Record W2735757171 · doi:10.3389/fenvs.2017.00041

Accounting for Carbon Stocks in Soils and Measuring GHGs Emission Fluxes from Soils: Do We Have the Necessary Standards?

2017· article· en· W2735757171 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

VenueFrontiers in Environmental Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsGreenhouse gasEnvironmental scienceSoil waterSoil carbonCarbon sequestrationSoil qualityClimate change mitigationContext (archaeology)StandardizationEnvironmental resource managementEnvironmental protectionSoil scienceComputer scienceCarbon dioxide

Abstract

fetched live from OpenAlex

Soil is a key compartment for climate regulation as a source of greenhouse gases (GHGs) emissions and as a sink of carbon. Thus, soil carbon sequestration strategies should be considered alongside reduction strategies for other greenhouse gas emissions. Taking this into account, several international and European policies on climate change are now acknowledging the importance of soils, which means that proper, comparable and reliable information is needed to report on carbon stocks and GHGs emissions from soil. It also implies a need for consensus on the adoption and verification of mitigation options that soil can provide. Where consensus is a key aspect, formal standards and guidelines come into play. This paper describes the existing ISO soil quality standards that can be used in this context, and calls for new ones to be developed through (international) collaboration. Available standards cover the relevant basic soil parameters including carbon and nitrogen content but do not yet consider the dynamics of those elements. Such methods have to be developed together with guidelines consistent with the scale to be investigated and the specific use of the collected data. We argue that this standardization strategy will improve the reliability of the reporting procedures and results of the different climate models that rely on soil quality data.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.585

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.221
Teacher spread0.207 · 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