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Record W3134850521 · doi:10.3390/agriculture11030218

Quantifying Root-Soil Interactions in Cover Crop Systems: A Review

2021· review· en· W3134850521 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

VenueAgriculture · 2021
Typereview
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCover cropEnvironmental scienceSoil organic matterSoil qualityNutrient cycleSoil carbonSoil biodiversityAgronomyEcosystemSoil waterAgroforestrySoil scienceEcologyBiology

Abstract

fetched live from OpenAlex

Plant roots are an integral part of soil ecosystems and contribute to various services, including carbon and nutrient cycling, weathering, and soil formation. They also modify soil physical properties (e.g., soil water content, pore size distribution, and bulk density) and impact subsequent crops’ growth. Cover crops have been reported to improve soil and environmental quality by reducing nutrient losses, improving soil water content, and increasing soil organic matter. Understanding the complex interactions between cover crop roots and soil (RS) is of utmost importance. However, cover crop RS interactions have not been critically reviewed. In this article, we investigated the nature of cover crop physical RS interactions and explored the emerging technologies for their study. We also assessed technologies that may be readily applied to the study of physical RS interactions in cover crop systems and discussed ways to improve related research in the future.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.466
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.068
GPT teacher head0.324
Teacher spread0.256 · 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