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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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 H 2 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.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.446
Threshold uncertainty score0.820

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.003
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