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Record W4245221515 · doi:10.1038/npre.2008.1741.1

Carbon Dioxide Splitting: A Summary of the Peer-Reviewed Scientific Literature

2008· preprint· en· W4245221515 on OpenAlexaff
Sierra Rayne

Bibliographic record

VenueNature Precedings · 2008
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsCarbon dioxideEnvironmental scienceCarbon fibersCarbon sequestrationAtmosphere (unit)Greenhouse gasEnvironmental chemistryNanotechnologyChemistryComputer scienceMaterials sciencePhysicsMeteorologyGeologyOceanography

Abstract

fetched live from OpenAlex

Abstract Increasing concentrations of carbon dioxide (CO2) in the atmosphere have stimulated significant global research and development efforts regarding the reduction in CO2 emissions from all point and non-point sources. In addition to technologies that do not use carbon feedstocks or which capture and "permanently" store CO2 (i.e., sequestration), there is considerable worldwide interest among the academic, industrial, and government communities regarding methods for dissociating waste stream carbon dioxide molecules into their constituent carbon and oxygen ("CO2 splitting") atoms as a final "end-of-pipe" treatment option. The splitting of carbon dioxide has also been actively discussed and researched in the space exploration and extraterrestrial colonization programs for several decades. This document summarizes the peer-reviewed open source scientific literature regarding carbon dioxide splitting.

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)0.004
metaresearch head score (Gemma)0.011
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: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0210.023
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0110.006

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 head0.012
GPT teacher head0.245
Teacher spread0.233 · 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
GenreReview

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

Citations6
Published2008
Admission routes1
Has abstractyes

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