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Record W4220946889 · doi:10.3390/su14053037

Agrivoltaics in Ontario Canada: Promise and Policy

2022· article· en· W4220946889 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSustainability · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicPhotovoltaic Systems and Sustainability
Canadian institutionsWestern University
Fundersnot available
KeywordsAgricultureBusinessRenewable energyRevenueAgricultural economicsNatural resource economicsGreenhouse gasElectricityEnvironmental protectionEconomicsEnvironmental scienceGeographyEngineering

Abstract

fetched live from OpenAlex

Well-intentioned regulations to protect Canada’s most productive farmland restrict large-scale solar photovoltaic (PV) development. The recent innovation of agrivoltaics, which is the co-development of land for both PV and agriculture, makes these regulations obsolete. Burgeoning agrivoltaics research has shown agricultural benefits, including increased yield for a wide range of crops, plant protection from excess solar energy and hail, and improved water conservation, while maintaining agricultural employment and local food supplies. In addition, the renewable electricity generation decreases greenhouse gas emissions while increasing farm revenue. As Canada, and Ontario in particular, is at a strategic disadvantage in agriculture without agrivoltaics, this study investigates the policy changes necessary to capitalize on the benefits of using agrivoltaics in Ontario. Land-use policies in Ontario are reviewed. Then, three case studies (peppers, sweet corn, and winter wheat) are analysed for agrivoltaic potential in Ontario. These results are analysed in conjunction with potential policies that would continue to protect the green-belt of the Golden Horseshoe, while enabling agrivoltaics in Ontario. Four agrivoltaic policy areas are discussed: increased research and development, enhanced education/public awareness, mechanisms to support Canada’s farmers converting to agrivoltaics, and using agrivoltaics as a potential source of trade surplus with the U.S.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.004
GPT teacher head0.196
Teacher spread0.192 · 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