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Record W2555753242 · doi:10.3303/cet1331003

Risk Assessment of CO2 Pipeline Network for CCS – A UK Case Study

2013· article· en· W2555753242 on OpenAlexaboutno aff
Chiara Vianello, Sandro Macchietto

Bibliographic record

VenuePadua Research Archive (University of Padova) · 2013
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsPipeline (software)Computer scienceOperating system

Abstract

fetched live from OpenAlex

Carbon Capture and Storage (CCS) requires new processes for the capture of CO2 using a variety of existing technologies and also potentially new processes which are still under development. Transport of CO2 in bulk, by pipeline from point sources or ship is also new processes and then can produce emerging risks. The majority of existing CO2 pipeline in the USA and Canada are located along with substantial infield pipe work for Enhanced Oil Recovery (EOR) projects (Kelliher et al, 2008; Kadnar, 2008). The USA experience cannot be easily applied to other regions or situations, in particular in Europe, because the CO2 pipelines in USA are located in areas with low population density. In fact, as stated in the report of the IPCC on CCS (IPCC, 2005), there is a lack of knowledge of safety concerning the pipeline transmission of CO2 in densely populated areas. External safety is one key aspect that should be assessed prior and during the operational phases of CO2 transport. Before starting the design a network, it is necessary select and identified the route corridor of the pipeline.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score0.732

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.032
GPT teacher head0.290
Teacher spread0.258 · 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 designSimulation or modeling
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

Citations2
Published2013
Admission routes1
Has abstractyes

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