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Coal and climate change

2025· book-chapter· en· W4408030474 on OpenAlexaff
Wu Yang, Ben Wang, Rajender Gupta

Bibliographic record

VenueEnergy and Climate Change · 2025
Typebook-chapter
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsClimate changeCoalEnvironmental scienceWaste managementGeologyEngineeringOceanography

Abstract

fetched live from OpenAlex

Coal plays an important role in the world energy system , and the carbon dioxide (CO 2 ) generated during its utilization has a significant impact on the global greenhouse effect and climate change . This chapter provides a comprehensive overview of the interrelationships between climate change, greenhouse gas emissions , coal utilization, and low-carbon technologies. It discusses the causes and consequences of climate change, emphasizing the significant impact of fossil fuel combustion, particularly coal, on global warming , and highlights the urgent need to address climate change, as rising levels of CO 2 concentration have disrupted the global carbon cycle and led to evident signs of global warming. It also emphasizes the importance of transitioning from coal to cleaner and more sustainable energy sources to mitigate the impact of climate change on the planet and future generations. The content delves into the role of coal in electricity production and heavy industry, acknowledging its historical importance while recognizing the environmental challenges it poses. It also discusses various approaches to reducing CO 2 emissions associated with coal consumption, such as integrated coal gasification combined cycle, integrated coal gasification fuel-cell combined cycle, carbon capture and storage , carbon capture and utilization technologies. This chapter emphasizes the need for continuous research and development of clean energy technologies and international cooperation to address the global challenges of climate change. Overall, people need to be more proactive and urgent in addressing climate change and transitioning towards low-carbon and sustainable energy in order to ensure a sustainable future for the planet.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0310.007

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 head0.024
GPT teacher head0.209
Teacher spread0.184 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2025
Admission routes1
Has abstractyes

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