MétaCan
Menu
Back to cohort
Record W4389485712 · doi:10.1002/saj2.20616

Sustaining organic matter in forest soils: What we have learned and what is left

2023· article· en· W4389485712 on OpenAlexaff
Cindy E. Prescott

Bibliographic record

VenueSoil Science Society of America Journal · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSoil waterSoil organic matterEnvironmental scienceOrganic matterLitterEnvironmental chemistryPhosphorusPlant litterMicroorganismEcosystemNutrientAgronomyEcologyChemistrySoil scienceBiology

Abstract

fetched live from OpenAlex

Abstract A concerted research effort over the last three decades has transformed our understanding of the processes through which soil organic matter (SOM) is formed. Although recalcitrant plant litter is important, especially for particulate organic matter, we now know that a large proportion of SOM, particularly the more persistent material associated with soil minerals, has been transformed by soil microorganisms. A major source of energy for these microorganisms is labile compounds that are exuded by plant roots and associated mycorrhizal fungi. Much of this exuded carbon (C) arises from surplus carbohydrates produced by plants growing under mild‐to‐moderate deficiencies of nitrogen, phosphorus, or water. Managing forests in a manner that sustain or enhance this flux of labile C from trees to soil would augment efforts to sequester more C in forest soils.

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)0.014
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.002
Science and technology studies0.0020.012
Scholarly communication0.0100.018
Open science0.0030.005
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0090.002

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 head0.017
GPT teacher head0.251
Teacher spread0.234 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations10
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueSoil Science Society of America JournalSame topicSoil Carbon and Nitrogen DynamicsFrench-language works237,207