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Record W1992164870 · doi:10.1016/j.egypro.2013.06.641

North West Sturgeon Refinery Project Overview - Carbon Capture Through Innovative Commercial Structuring in the Canadian Oil Sands

2013· article· en· W1992164870 on OpenAlexfundaboutno aff
Kevin Heal, Terry Kemp

Bibliographic record

VenueEnergy Procedia · 2013
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsnot available
FundersGovernment of Alberta
KeywordsOil refineryRefineryEnvironmental scienceCarbon capture and storage (timeline)Oil sandsWaste managementCarbon footprintGeneral partnershipPetroleumFossil fuelAsphaltGreenhouse gasEngineeringClimate changeBusinessGeographyGeology

Abstract

fetched live from OpenAlex

North West Redwater Partnership (NWR) is building the world's first direct to fuels bitumen refinery to combine gasification technology with an integrated carbon capture and storage program. When complete, the first phase of the refinery will produce a range of refined petroleum products with the advantage of having both higher added value and a lower carbon footprint than traditional upgraders or refineries. This project overview will profile the NWR project and discuss the innovative technological approach to incorporate large scale carbon capture in a greenfield Canadian oil sands development.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.251
Threshold uncertainty score0.506

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.028
GPT teacher head0.275
Teacher spread0.247 · 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
GenreOther

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
Published2013
Admission routes2
Has abstractyes

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