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Record W1995184931 · doi:10.4271/2012-36-0199

Innovative Solution for the Valve Lifts Variation of Combustion Engines

2012· article· en· W1995184931 on OpenAlexaff
Juliano Savoy, Mauro Moraes de Souza, Tadeu Geraldo Domingues

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2012
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsWeyerhauser (Canada)
Fundersnot available
KeywordsVariation (astronomy)CombustionAutomotive engineeringComputer scienceEnvironmental scienceEngineeringChemistryPhysics

Abstract

fetched live from OpenAlex

The constant search for more efficient combustion engines with lower levels of CO₂ emissions has contributed to the development of new technologies that could reach severe global environment targets. Most of the new technologies are related to the lift and timing variation of the opening and closing of the intake valves, through variable camshafts. The controlled lift and timing variation allows the air-fuel mixture to be optimized for specific working conditions of the engine without the driver's perception. This paper presents a new design and a new operation concept for the lift variation of the intake valve. The technical and economical feasibility analysis of this new design is done through virtual studies and prototypes in the Alpha phase of the project. The valve lift control optimizes the fuel consumption, and consequently, it reduces the levels of CO₂ emissions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.260
Teacher spread0.242 · 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 designBench or experimental
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

Citations0
Published2012
Admission routes1
Has abstractyes

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