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Record W4413768242 · doi:10.5539/ijc.v17n2p90

Develop Energy Production New Channels

2025· article· en· W4413768242 on OpenAlexvenueno aff
J. Jin

Bibliographic record

VenueInternational Journal of Chemistry · 2025
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryProduction (economics)Energy (signal processing)Biochemical engineeringMicroeconomics

Abstract

fetched live from OpenAlex

Cement and steel production, it released a large number of CO2 (about 4.5-5 billion tons/year), serious air pollution. The making use of Carbon Gasification Reaction-CGR (CO2 + C = 2 CO - 162.4 kj/mol) to convert the CO2 into gas CO, can get 4.581- 5.09 trillion M3 CO gas, It is equivalent to 1,6 to 1,8 Billion M3 energy of natural gas, which is equivalent to the annual transportation capacity of about 30 Nord Stream No2 lines. Abundant reserves of limestone and iron ore have become raw materials for fuel production. The Water Gas Reaction-WGR ( C+H2O=H2+CO - 118.82kj/mol) can be utilized to produce gas using green energy sources such as firewood, plastics, and rubber etc.,Due to its abundant resources, low cost and significant reduction in CO2 emissions, the author believes that this reaction can save the Earth and humanity.

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 score0.731
Threshold uncertainty score0.382

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 head0.009
GPT teacher head0.264
Teacher spread0.256 · 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
Published2025
Admission routes1
Has abstractyes

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