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Record W2978530240 · doi:10.11575/prism/37176

Reversible Solid Oxide Fuel Cell Technology for Carbon Utilization in Alberta

2019· article· en· W2978530240 on OpenAlexaboutno aff
Abraham Omar Masri

Bibliographic record

VenueOpen MIND · 2019
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsnot available
Fundersnot available
KeywordsCarbon fibersFuel cellsSolid oxide fuel cellOxideEnvironmental scienceWaste managementMaterials scienceChemistryChemical engineeringMetallurgyEngineeringComposite number

Abstract

fetched live from OpenAlex

Alberta’s economy is heavily dependent on the oil & gas sector, and with increasing concern over climate change and global warming from anthropogenic CO2 in the atmosphere, there is an urgent need for decarbonizing the economy. Progress toward decarbonization has been made with the Alberta Carbon Trunk Line facilitating carbon capture, utilization and storage; however, additional clean-technology for carbon utilization is required to reduce greenhouse gas emissions while allowing continued oil production to meet the growing energy needs of the world. This study analyzes three models assessing Reversible Solid Oxide Fuel Cells (RSOFCs) in Alberta as a carbon utilization technology, with the ability to use waste CO2 while producing fuels, and chemicals; or as means to generate clean electricity. This study seeks to ascertain the environmental, economic, and energy, implications of this technology. The findings indicate that the technology is economically valuable, while providing environmental benefits and substantial energy applications.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.431

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.319
Teacher spread0.285 · 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 designBench or experimental
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
Published2019
Admission routes1
Has abstractyes

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Same venueOpen MINDSame topicAdvancements in Solid Oxide Fuel CellsFrench-language works237,207