MétaCan
Menu
Back to cohort
Record W3185765301 · doi:10.3390/su13158185

Soil Nutrient Supply in Cultivated Bush Bean–Potato Intercropping Grown in Subarctic Soil Managed with Agroforestry

2021· article· en· W3185765301 on OpenAlexafffundabout
Jim D. Karagatzides, Meaghan J. Wilton, Leonard J. S. Tsuji

Bibliographic record

VenueSustainability · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsUniversity of TorontoGeorgian College
FundersCanadian Institutes of Health Research
KeywordsIntercroppingNutrientAgronomyEnvironmental scienceWindbreakSoil waterAgroforestrySubarctic climateMicroclimateDitchGrowing seasonBiologyEcology

Abstract

fetched live from OpenAlex

To address food insecurity in northern Canada, some isolated communities started gardening initiatives to reduce dependencies on expensive foods flown in to communities. From 2012–2014, soils in northern Ontario James Bay lowlands were cultivated with bush beans and potatoes, grown in sole and intercropping configurations, in an open field and an agroforestry system enclosed by willow trees. The objective of this study was to compare the supply rates of 15 plant-available nutrients in these soils using in situ ion exchange membranes. After three years of cultivation, the agroforestry site had significantly greater supply of PO4, Ca, and Zn and these nutrients had positive correlations with yield. By contrast, the open site had significantly greater supply of Mg, SO4, and B; these nutrients, and Al, had negative correlations with yield. Whilst there were no differences between sole and intercropping configurations, significantly greater supply of NO3, Ca, Cu, Fe, and Zn occurred early in the growing season, compared to significantly greater supply of K, SO4, B, and Al later in the season. Significantly greater yields have been harvested in the agroforestry site and it is suspected that the presence of a willow shelterbelt improves the microclimate and plant-available PO4, Ca, and Zn.

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 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)0.001
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 score0.026
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.225
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 teacher head, 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

Citations6
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueSustainabilitySame topicAgronomic Practices and Intercropping SystemsFrench-language works237,207