MétaCan
Menu
Back to cohort
Record W3091851995 · doi:10.1002/agg2.20109

Fertilizing bush beans with locally made compost in a remote subarctic community

2020· article· en· W3091851995 on OpenAlexafffund
Meaghan J. Wilton, Jim D. Karagatzides, Leonard J. S. Tsuji

Bibliographic record

VenueAgrosystems Geosciences & Environment · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsGeorgian CollegeUniversity of Toronto
FundersInstitute of Indigenous Peoples' HealthCanadian Institutes of Health Research
KeywordsCompostAmendmentAgronomyEnvironmental scienceNutrientPhaseolusBiomass (ecology)CropGreen wasteBiologyEcology

Abstract

fetched live from OpenAlex

Abstract High latitude communities are cultivating crops to adapt to global warming, and thereby reduce dependency on food importation. To minimize the dependency of imported soil nutrient amendments for crop production, the Indigenous subarctic community of Fort Albany First Nation generated compost using by‐products from the traditional activities of goose harvesting along with other organic waste within the community. The compost was evaluated in a single growing season pot experiment as an amendment for bush beans ( Phaseolus vulgaris L.) by being mixed with the local Terric Haplosaprist edaphic soil that was P and K deficient. Twelve pots growing bush beans were amended with compost at rates ranging from 3 to 30% and with unamended controls. All eight plant metrics (height, aboveground, leaf and bean biomass, quantity of leaves and pods, and individual and summed leaf surface area) showed a significant positive relationship with increasing compost amendments ( p ≤ .0025, r 2 = .66–.86), suggesting soils with compost attain greater bean yields than unamended soil. A threshold of bean growth was not reached, implying that compost amendments >30% may provide even greater bean yield. However, the application of P and K with the 30% compost addition exceeds recommended rates, suggesting that nutrient availability was hindered. Notwithstanding logistical issues in scaling‐up to amend all gardens in the community, such as improving the compost quality and quantity, composting using Indigenous harvest by‐products and local organic wastes is a promising adaptive food security strategy.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.795
Threshold uncertainty score0.985

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 studies0.0000.000
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 head0.033
GPT teacher head0.206
Teacher spread0.172 · 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

Citations4
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueAgrosystems Geosciences & EnvironmentSame topicAgronomic Practices and Intercropping SystemsFrench-language works237,207