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Record W4292426541 · doi:10.1063/5.0093305

Review on coal-fired power plants from post-combustion CO2 process and challenges

2022· article· en· W4292426541 on OpenAlexaff
Oluranti Agboola, Mapula Lucey Moropeng, O.S.I. Fayomi, J.A. Oyebanji, K. M. Oluwasegun

Bibliographic record

VenueAIP conference proceedings · 2022
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsFlue gasPower stationCombustionCoalCarbon capture and storage (timeline)Process engineeringAtmosphere (unit)Waste managementProcess (computing)Environmental scienceCarbon dioxideFlue-gas emissions from fossil-fuel combustionClean coal technologyPower (physics)Computer scienceEngineeringChemistryElectrical engineering

Abstract

fetched live from OpenAlex

The capturing of CO2 from power plant flue gases offers unique chance to alleviate the emissions of coal-fired power plants to the environment. The fraction of CO2 captured and the increased production of CO2 that results from loss in the whole efficiency of power plants are determinant factors for the net emissions reduction to the atmosphere via carbon dioxide capture storage. Post-combustion capture is of great interest as it is easy to implement as to existing power plants. The use of post combustion capture in power plant was reviewed. The challenges of post combustion process were reviewed with possible solutions.

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)0.001
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: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.026
GPT teacher head0.229
Teacher spread0.203 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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