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Record W4285042061 · doi:10.3389/fenvs.2022.890104

Chile and its Potential Role Among the Most Affordable Green Hydrogen Producers in the World

2022· article· en· W4285042061 on OpenAlexaff
Kevin Acosta, Iván Salazar, Manuel Saldaña, Jahir Ramos, Alessandro Navarra, Norman Toro

Bibliographic record

VenueFrontiers in Environmental Science · 2022
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsMcGill University
FundersUniversidad de Antofagasta
KeywordsRenewable energyContext (archaeology)Natural resource economicsClimate changeProduction (economics)Hydrogen productionEnvironmental scienceGlobal warmingBusinessEnvironmental protectionHydrogenGeographyEconomicsEngineeringEcologyChemistry

Abstract

fetched live from OpenAlex

As result of the adverse effects caused by climate change, the nations have decided to accelerate the transition of the energy matrix through the use of non-conventional sources free of polluting emissions. One of these alternatives is green hydrogen. In this context, Chile stands out for the exceptional climate that makes it a country with a lot of renewable resources. Such availability of resources gives the nation clear advantages for hydrogen production, strong gusts of wind throughout the country, the most increased solar radiation in the world, lower cost of production of electrical supplies, among others. Due to this, the nation would be between the lowest estimated cost for hydrogen production, i.e., 1.5 USD/kg H2 approximately, scenario that would place it as one of the cheapest green hydrogen producer in the world.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.002

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 head0.003
GPT teacher head0.169
Teacher spread0.166 · 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
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

Citations21
Published2022
Admission routes1
Has abstractyes

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