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Record W4399246271 · doi:10.1002/ece2.46

Coal dilemma: Is in situ clean power plant a way out?

2024· article· en· W4399246271 on OpenAlexaff
Baisheng Nie, Liangliang Jiang, Xianfeng Liu, Bozhi Deng, Peng Liu, Hao Zhang, Suihong Song, Yan Ke, Jiansheng Zhang, Peng Liu, Zhangxin Chen, S.M. Farouq Ali

Bibliographic record

VenueEcoEnergy · 2024
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDilemmaClean coalCoalWaste managementEnvironmental sciencePower stationIn situPower (physics)Clean-upEngineeringChemistryElectrical engineeringMathematicsPhysics

Abstract

fetched live from OpenAlex

Abstract The global shift toward cleaner energy sources, driven by carbon neutrality goals and climate change urgency, faces a paradoxical rise in coal consumption despite efforts to expand alternative energies. Economic disparities drive reliance on coal, particularly in underdeveloped regions where affordability and accessibility dictate energy choices. To address this, innovative approaches such as harnessing controlled pulverized coal detonation for in situ clean power plants are proposed. These plants offer compact, efficient, and sustainable energy generation with reduced emissions and minimal environmental impact. In addition, a comparison of costs, efficiency, and environmental impact with conventional methods showcases the potential of this novel technology to transform coal‐based energy into a green and viable solution.

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)0.000
metaresearch head score (Gemma)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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 designNot applicable
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

Citations10
Published2024
Admission routes1
Has abstractyes

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