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Record W7115203642

Carbon Capture and Storage:Realising the Potential?

2012· book· en· W7115203642 on OpenAlexaff

Bibliographic record

VenueEdinburgh Research Explorer · 2012
Typebook
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsCentre for Global Health Research
FundersBritish Geological SurveyUniversity of SussexImperial College LondonUniversity of LeedsUK Energy Research CentreDepartment of Energy and Climate ChangeNatural Environment Research CouncilU.S. Department of Energy
KeywordsCarbon capture and storage (timeline)Carbon fibersComponent (thermodynamics)Greenhouse gasProduction (economics)Emerging technologiesTechnology assessmentEnergy system
DOInot available

Abstract

fetched live from OpenAlex

The aim of the research is to assess the technical, economic, financial and social uncertainties facing carbon capture and storage (CCS) technologies, and to analyse the potential role they could play in the UK power sector between now and 2030. CCS technologies are often highlighted as a crucial component of future low carbon energy systems – in the UK and internationally. However, it is unclear when these technologies will be technically proven at full scale, and whether their costs will be competitive with other low carbon options.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0050.013
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0260.008

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 head0.047
GPT teacher head0.279
Teacher spread0.233 · 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
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

Citations0
Published2012
Admission routes1
Has abstractyes

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