MétaCan
Menu
Back to cohort
Record W4313528549 · doi:10.1021/cen-10101-buscon9

Svante raises funds for carbon capture

2023· article· en· W4313528549 on OpenAlexaboutno aff
Craig Bettenhausen

Bibliographic record

VenueC&EN Global Enterprise · 2023
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsFlue gasWaste managementNatural gasChevron (anatomy)TonneSorbentCarbon fibersEnvironmental scienceSan JoaquinEngineeringBusinessNatural resource economicsEconomicsChemistryMaterials scienceGeology

Abstract

fetched live from OpenAlex

The carbon-capture-technology firm Svante has raised $318 million in a series E funding round led by Chevron. Svante says it will invest the money in its facility in Vancouver, which is designed to produce enough sorbent modules to capture 1 million metric tons of carbon dioxide per year. The firm is targeting industrial sources of CO 2 , such as chemical plants and factories making hydrogen, paper, cement, and metals. Svante is also exploring direct air capture of CO 2 . Chevron plans to start testing Svante’s process on a natural gas combustion flue stream in California’s San Joaquin Valley in the next few weeks.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score1.000

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 head0.008
GPT teacher head0.235
Teacher spread0.227 · 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.

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueC&EN Global EnterpriseSame topicCarbon Dioxide Capture TechnologiesFrench-language works237,207