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Record W4401073570 · doi:10.1021/cen-10223-buscon6

Methanex plans Alberta carbon capture

2024· article· en· W4401073570 on OpenAlexaboutno aff
Alex Tullo

Bibliographic record

VenueC&EN Global Enterprise · 2024
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceCarbon fibersComputer science

Abstract

fetched live from OpenAlex

Methanex and the carbon capture technology firm Entropy are launching a front-end engineering and design study for a carbon capture plant at Methanex’s methanol facility in Medicine Hat, Alberta. The plant will use Entropy’s technology to capture carbon dioxide from combustion. The system that the firms plan to install will cost about $75 million and capture about 400 metric tons (t) of CO 2 per day. Methanex will use some of this CO 2 to make 50,000 t of methanol per year, while the rest will be stored underground. Conventional methanol is made by reacting carbon monoxide with hydrogen. Alberta has been attracting investment in carbon capture: In June, Shell gave the green light to Polaris, a project for its Scotford refining and petrochemical complex that will capture and store 650,000 t of CO 2 per year. And late last year, Dow’s board approved a $6.5 billion investment to build

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.806
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.252
Teacher spread0.246 · 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 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
Published2024
Admission routes1
Has abstractyes

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