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Record W4380083943 · doi:10.54254/2753-8818/5/20230448

Comparative Study on the Performance of Traditional Engines and Various Substitutes

2023· article· en· W4380083943 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

VenueTheoretical and Natural Science · 2023
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInternal combustion engineCombustionAutomotive industryFossil fuelAutomotive engineeringElectric motorAutomotive engineEnvironmentally friendlyEngineeringMechanical engineeringWaste management

Abstract

fetched live from OpenAlex

As the global climate starts to change due the exploitation of natural resources by human, internal combustion engines are no longer the favorite son of mankind. Instead, alternatives such as hybrid power systems and electric motors have drawn the attention of various car manufacturers and numerous scholars from worldwide. At the same time, the automobile industry has not given up internal combustion engines yet, and kept producing innovative engine designs aiming to minimize the negative impact of fossil-fuels on the environment. By researching, analyzing, and comparing data and information from various sources, this article will discuss the fundamentals and working basics of internal combustion engines, hybrid power systems and electric motors, the iconic innovations on internal combustion engines by several car manufacturers, and will compare traditional engines and its alternatives through various aspects. This essay will mainly focus on internal combustion engines and some of the more environmentally friendly alternatives available today, as well as a comparison between them and their advantages and disadvantages.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.926
Threshold uncertainty score0.796

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 studies0.0000.002
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 head0.021
GPT teacher head0.250
Teacher spread0.229 · 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