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Record W6990742282

The effects of UV-B radiation on crop yields across 4 countries from 1966-2021

2023· article· en· W6990742282 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship @ Claremont (The Claremont Colleges) · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
Fundersnot available
KeywordsOzone layerCropClimate changeOzone depletionYield (engineering)Crop yieldGovernment (linguistics)Crop lossOzoneAgriculture
DOInot available

Abstract

fetched live from OpenAlex

In the late 1970s, one of the most serious environmental issues was the hole in the ozone. Scientists proved that ozone depletion was caused by the chlorofluorocarbons (CFCs) produced by factories and that it was causing an increase in UV-B radiation, a serious cause of skin cancer. The Montreal Protocol (1987) was a groundbreaking policy that called for an immediate halt in CFC production. Although the ozone hole has begun shrinking, its interactions with global climate change are much less understood and can have major influences on human health. One of these factors is accessibility to food. The effects of UV-B radiation on crop yields are poorly researched and understood. Some lab experiments have been criticized for having defective methods creating biased results. Additionally, the results produced cannot be translated to other plants as UV-B radiation effects are species dependent. This new review and analysis study aims to discover the effects of UV-B radiation on crop yields using crop yield data. This study concludes that there is no statistically significant impact of ozone concentration on crop yields. Despite that this study is based on the best available data on ozone concentration, it must be recognized that it is limited as only 8 ground-based monitoring stations exist around the world. The results stress the importance of continued stratospheric ozone monitoring as climate change worsens. This study is a call to action for government agencies to invest more resources in this endeavor.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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 score0.261
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.012
GPT teacher head0.244
Teacher spread0.232 · 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.

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
Published2023
Admission routes1
Has abstractyes

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