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Record W1520843488 · doi:10.4271/2000-01-0671

Development of the High Speed 2ZZ-GE Engine

2000· article· en· W1520843488 on OpenAlexaboutno aff
Takasuke Shikida, Yoshikatsu Nakamura, Tamio Nakakubo, Hiroyuki Kawase

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2000
Typearticle
Languageen
FieldEngineering
TopicTechnical Engine Diagnostics and Monitoring
Canadian institutionsnot available
FundersYamaha Motor Company
KeywordsComputer scienceAutomotive engineeringElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

The 2ZZ-GE is a sporty 1.8 liter engine based on the 1ZZ-FE, which is currently being mass produced in Japan, USA, and Canada. It was designed to fit into the same engine compartment as the base 1ZZ-FE, have equivalent vehicle performance as a 2.2 liter engine, and meet TLEV emission standards. The main features of the 2ZZ-GE are the Metal Matrix Composite (MMC) reinforced all-aluminum cylinder block and the intelligent Variable Valve Timing and Lift (VVTL-i) system. These features were adopted for size and performance. Other features such as a reinforced ladder frame, and an intake manifold spacer was utilized for a sporty engine sound. The 2ZZ-GE delivers maximum power at 7600rpm and maximum torque at 6800rpm.

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)0.000
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.008
GPT teacher head0.212
Teacher spread0.204 · 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

Citations9
Published2000
Admission routes1
Has abstractyes

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