MétaCan
Menu
Back to cohort
Record W2362918992

Advantages and Application of Linear Induction Motor in Urban Transit System

2008· article· en· W2362918992 on OpenAlexaboutno aff
Hui Zeng

Bibliographic record

VenueConverter Technology & Electric Traction · 2008
Typearticle
Languageen
FieldEngineering
TopicRailway Systems and Energy Efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsBogieLinear induction motorUrban rail transitUrban railUrban transitLinear motorAutomotive engineeringTraction motorRail transitTransport engineeringEngineeringTransit systemTraction (geology)Transit (satellite)Induction motorPublic transportMechanical engineeringElectrical engineeringVoltage
DOInot available

Abstract

fetched live from OpenAlex

The linear induction motor (LIM) wheel-rail system is regarded as an advanced mode of resource-saving urban rail transit forthe advantages of low cost and great line applicability. It analyses the technical characteristics and performance of LIM metro vehicle's bogie,traction and brake in Japan and Canada. The economy and applicability of LIM in urban rail transit are discussed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.004
GPT teacher head0.181
Teacher spread0.177 · 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
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

Citations1
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueConverter Technology & Electric TractionSame topicRailway Systems and Energy EfficiencyFrench-language works237,207