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Record W4379232029 · doi:10.3390/biomass3020012

Maximizing Biomass with Agrivoltaics: Potential and Policy in Saskatchewan Canada

2023· article· en· W4379232029 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBiomass · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicPhotovoltaic Systems and Sustainability
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRevenueLegislationZoningAgricultural economicsBiomass (ecology)LivestockAgricultureForagePastureCropBusinessYield (engineering)GeographyAgroforestryEnvironmental protectionAgricultural scienceEnvironmental scienceAgronomyForestryEconomics

Abstract

fetched live from OpenAlex

Canada is a leading global agricultural exporter, and roughly half of Canada’s farmland is in Saskatchewan. New agrivoltaics research shows increased biomass for a wide range of crops. This study looks at the potential increase in crop yield and livestock in Saskatchewan through agrivoltaics along with its financial implications. Then, the legislation that could influence the adoption of agrivoltaics in Saskatchewan is reviewed. Specifically, experimental results from agrivoltaic wheat production are analyzed for different adoption scenarios. The impact of converting the province’s pasture grass areas to agrivoltaics and using sheep to harvest them is also examined. The results indicate that approximately 0.4 million more tons of wheat, 2.9 to 3.5 million more tons of forage and 3.9 to 4.6 million additional sheep can be grazed using agrivoltaics in Saskatchewan. Only these two agrivoltaics applications, i.e., wheat farmland and pastureland, result in potential additional billions of dollars in annual provincial agricultural revenue. The Municipalities Act and the Planning and Development Act were found to have the most impact on agrivoltaics in the province as official community plans and zoning bylaws can impede diffusion. Agrivoltaics can be integrated into legislation to avoid delays in the adoption of the technology so that the province reaps all of the benefits.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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