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Record W2919308704 · doi:10.1002/er.4435

Review of climate change issues: A forcing function perspective in agricultural and energy innovation

2019· article· en· W2919308704 on OpenAlexaff
İlhami Yıldız

Bibliographic record

VenueInternational Journal of Energy Research · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicWater-Energy-Food Nexus Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsNatural resource economicsClimate changeFood securityBusinessAgricultureResilience (materials science)Food systemsPopulationClimate change mitigationWorld populationEnvironmental resource managementEnvironmental scienceEconomicsGeographyDeveloping countryEconomic growthEcology

Abstract

fetched live from OpenAlex

Climate change is observed globally, and the projections predict that the change will continue in the future for quite a long time. The mitigation and adaptation to climate change, however, are offering tremendous business opportunities around the world, especially for businesses operating in the agri-food, energy, finance, and health sectors, water infrastructure, built environments, and other relevant services. When the severity of heat waves is considered, for instance, it would become quite clear that the demand for cooling would accelerate, putting further stress on energy supply and increasing the risk of electricity black outs. Similarly, the projections also provide warnings about increased drought risk in many regions around the globe, and even worse, it should also be emphasized that 60% more food will be needed globally, while 100% more demand for food is projected in developing countries by the year 2050. While all these are being projected, we are experiencing progressively increasing stress on our global freshwater resources, which are worsened further by climate change-driven impacts and water pollution. Consequently, reducing agri-food production systems' susceptibility to climate change and strengthening the resilience of such systems are extremely important to sustain and improve the livelihoods of billions of people around the globe. Moreover, reducing emissions due to fossil fuels consumption and production is vital for the whole global population, and agri-food and energy sectors have tremendous potentials for reducing inefficiencies and emissions while simultaneously playing their crucial roles in food and energy security as well as poverty reduction. Both of these sectors are facing significant climate change-driven challenges, which provide ample opportunities for cutting-edge novel knowledge and innovative products, processes, services, and policies. And due to the reciprocal relationships between climate change and agri-food and energy innovations, in return, complementing the other forms, such innovations will speed up the climate change mitigation and adaptation processes.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.056
GPT teacher head0.359
Teacher spread0.303 · 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 designTheoretical or conceptual
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

Citations28
Published2019
Admission routes1
Has abstractyes

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