MétaCan
Menu
Back to cohort
Record W4389056100 · doi:10.1038/s44296-023-00003-7

“Reactive Mineral Sink” drives soil organic matter dynamics and stabilization

2023· article· en· W4389056100 on OpenAlexaff
Songlin Wu, Kurt O. Konhauser, Baodong Chen, Longbin Huang

Bibliographic record

Venuenpj Materials Sustainability · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsUniversity of Alberta
FundersAustralian Research Council
KeywordsBiogeochemical cycleOrganic matterEnvironmental scienceSoil organic matterSoil waterCarbon sequestrationChemistrySoil scienceEnvironmental chemistryCarbon dioxide

Abstract

fetched live from OpenAlex

Abstract Reactive primary and secondary minerals play a critical role in the transformation and stabilization of organic matter (OM) in soil, a critical aspect that has been largely overlooked in existing literature. In this regard, we propose a new model known as the “reactive mineral sink” (RMS) to illustrate three primary mechanisms through which these minerals drive the bioprocessing, transformation, transport and stabilization of OM in soil. Firstly, from a biological perspective, reactive minerals influence enzymatic and microbial OM processing through binding enzymatic proteins or influencing the structure of microbial communities. Secondly, from a chemical standpoint, these minerals have the capacity to adsorb OM and/or coprecipitate with it, leading to a more diverse distribution of OM in the soil. This distribution, in turn, triggers OM transformation through chemical catalysis and redox reactions. Thirdly, on a physical level, reactive minerals have a substantial impact on soil architecture, aggregate dynamics, porosity development, and hydrological processes. These physical changes then affect the transport, reprocessing and stabilization of OM. The RMS model provides a conceptual framework that underscores the fundamental role of reactive minerals in driving the dynamics of OM and carbon (C) sequestration in natural soil. Furthermore, it promotes the restoration of soil biogeochemical processes and ecological resilience. We advocate for the implementation of strategies based on the RMS model to enhance the sequestration of organic C in soils for the purposes of rejuvenating soil health and mitigating CO2 emission.

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 score0.003
Threshold uncertainty score0.008

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.004
GPT teacher head0.219
Teacher spread0.215 · 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

Citations74
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuenpj Materials SustainabilitySame topicArsenic contamination and mitigationFrench-language works237,207