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Record W1936388281 · doi:10.1002/ghg.1501

Greenhouse gas (GHG) emissions in the Sultanate of Oman

2015· article· en· W1936388281 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

VenueGreenhouse Gases Science and Technology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Waterloo
FundersSultan Qaboos UniversityUniversity of BathUnited Nations Development ProgrammeGlobal Environment Facility
KeywordsGreenhouse gasFossil fuelGross domestic productEnvironmental scienceNatural gasNatural resource economicsEnvironmental protectionOil and natural gasFugitive emissionsClimate changeAgricultural economicsWaste managementEngineeringEconomicsEconomic growthEcology

Abstract

fetched live from OpenAlex

Abstract Worldwide, many countries are being affected by greenhouse gas (GHG) emissions. The Sultanate of Oman is no exception. In Oman, both oil‐ and natural‐gas‐related activities have the most important shares of the nation's Gross Domestic Product (GDP). Hence, they are expected to be the primary cause of GHG emissions within the country. In this study, the greenhouse carbon dioxide emissions (CO 2 ) released from the fossil fuels (i.e., oil and natural gas) used in the country for energy production purposes was computed by using the Intergovernmental Panel on Climate Change (IPCC) reference approach for National Greenhouse Gas Inventories. The objective was to develop the CO 2 emissions for Oman over the last 40 years starting from year 1972. The obtained results indicated that Oman has a growth in its CO 2 GHG emissions. This study is very important and essential, as it will assist Oman to monitor its progress in reducing CO 2 emissions. © 2015 Society of Chemical Industry and John Wiley & Sons, Ltd

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.004
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 head0.013
GPT teacher head0.225
Teacher spread0.212 · 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