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Record W4387065460 · doi:10.15446/dyna.v90n226.105963

Sustainability and future of the oil and gas industry: a mini-review

2023· article· en· W4387065460 on OpenAlexaff
Evanna Dadd, Victoria Kirou, J. Velásquez, Sadafnaz Kashi Kalhori, Daniela Galatro

Bibliographic record

VenueDYNA · 2023
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGeopoliticsRenewable energySustainabilityEnergy transitionWork (physics)Natural resource economicsFossil fuelSustainable developmentBusinessResilience (materials science)Hydrogen economyGreenhouse gasPsychological resilienceEnergy engineeringEconomicsEnvironmental economicsEconomic systemPolitical scienceEngineeringFuel cellsHydrogen fuelWaste managementPolitics

Abstract

fetched live from OpenAlex

This work presents a global perspective on the future of the oil and gas industry by exploring the role of energy companies in navigating energy transition, given their historical prominence in actively contributing to the ongoing climate crisis to meet growing energy demand. The current oil and gas industry is perceived as incompatible with sustainable development as society turns increasingly towards renewable technologies. The development and integration of renewable technologies such as carbon capture, nanoparticles, and hydrogen are essential for key energy players to reposition themselves successfully and sustainably amidst energy diversifications. Geopolitical, economic, and technological factors influence these strides toward co-existing in a more prospective energy mix. The duality of geopolitical dynamics is manifested through positive or negative policy advocacy for energy integration. Hence, it dictates energy companies' economic resilience into more low-carbon, hybrid renewable technological investments and operations.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0000.001
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.286
Teacher spread0.275 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

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