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Record W4319598978 · doi:10.6000/1929-6002.2023.12.01

A Comparative Study on the Renewable Energy Related Curriculums in the Universities in Guangdong- Hong Kong- Macao Greater Bay Area

2023· article· en· W4319598978 on OpenAlexvenueno aff
Chao-chen Chung, Zhong Yujia

Bibliographic record

VenueJournal of Technology Innovations in Renewable Energy · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsnot available
Fundersnot available
KeywordsBayRenewable energyCurriculumSustainabilityGeographySustainable energyBusinessPolitical scienceEconomic growthEngineeringCivil engineeringEconomicsElectrical engineeringEcology

Abstract

fetched live from OpenAlex

The development of energy professionals played important roles for energy innovation and sustainability transitions in Guangdong- Hong Kong- Macao Greater Bay Area. We selected three representative universities, i.e. Sun Yat-sen University, the Chinese University of Hong Kong, and the University of Macao in Guangdong, Hong Kong and Macao as the examples which presented current status of higher education in the fields of renewable energies. We compared these renewable energy related curriculums in terms of quantities, structures and contents. The results showed that the renewable energy related curriculums in the three universities should expand at postgraduate levels, strengthen their linkages with industries and increase interdisciplinary courses in order to optimize professional training in the Greater Bay Area.

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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.844
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.019
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.037
GPT teacher head0.308
Teacher spread0.272 · 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 designQualitative
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

Citations1
Published2023
Admission routes1
Has abstractyes

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