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Record W4385810768 · doi:10.1021/cen-10126-buscon2

Nutrien shelves low-carbon ammonia project in Louisiana

2023· article· en· W4385810768 on OpenAlexaboutno aff
Alex Tullo

Bibliographic record

VenueC&EN Global Enterprise · 2023
Typearticle
Languageen
FieldChemical Engineering
TopicAmmonia Synthesis and Nitrogen Reduction
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceTonneAmmoniaWork (physics)Waste managementBusinessNatural resource economicsEconomicsEngineeringChemistry

Abstract

fetched live from OpenAlex

Citing volatility in fertilizer markets, Nutrien has decided to suspend work on a low-carbon ammonia project planned for its complex in Geismar, Louisiana. In the Canadian company’s Aug. 2 earnings statement , CEO Ken Seitz says the move is meant to “reduce our controllable costs.” The cost of building the plant has increased from initial estimates, the company says. Nutrien also points to uncertainty around the timing of demand for low-carbon ammonia, which is intended to be exported for use as a fuel, primarily in East Asia. When Nutrien announced it was studying the project in May 2022, it estimated the cost at $2 billion. It planned an ammonia plant with 1.2 million metric tons (t) of annual capacity. An autothermal reformer was to produce hydrogen raw material from natural gas, and the firm would recover the by-product carbon dioxide. Overall, Nutrien aimed to recover 90% of the CO 2

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score0.894

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.254
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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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