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Record W6998797096

Arthropod Diversity Within The Three Sisters Cropping System

2024· other· en· W6998797096 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionExclosureTSG101Hyporeflexia
DOInot available

Abstract

fetched live from OpenAlex

The Three Sisters is an indigenous cropping method that dates back hundreds of years. It is comprised of the simultaneous planting of corn, bean, squash, and sometimes sunflower. However, there has been no published research into arthropod communities and interactions with this cropping system. My study examined arthropod abundance and taxa to the family level at three areas: uncultivated, fields planted with The Three Sisters, and field edges. This was done at three sites in Manitoba: Ian N. Morrison Research Farm near Carman, Glenlea Research Station near Glenlea, and Brokenhead Ojibway First Nations Reserve. I placed 8 sticky cards within each area at each site starting in July 2023, and had 4 bi-weekly sampling rounds. The number of samples collected and processed was 288. I conducted a perMANOVA test, and ran multiple negative binomial generalized linear mixed models, testing the abundance and number of taxa present in relation to the site, area type, date, colour, and using trap number as a random effect. All sites were significantly different from each other. Glenlea had the highest diversity, and Carman had the least diversity. The uncultivated areas differed from both the field and edge areas, and the fields and edges also differed from each other at all sites. The field and edges had higher diversity than the uncultivated areas. The most important finding of my study was that The Three Sisters is an agricultural method that can allow for higher diversity of arthropods than uncultivated areas.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.198
Teacher spread0.175 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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