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Designing a Composite Material for Use in Brake Applications

2005· article· en· W1971820706 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

VenueMaterials science forum · 2005
Typearticle
Languageen
FieldEngineering
TopicBrake Systems and Friction Analysis
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsMaterials scienceBrakeCast ironComposite numberAutomotive industryAutomotive engineeringBrake padBrake shoeRotor (electric)AluminiumMechanical engineeringComposite materialMetallurgyEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

Traditionally, automotive brake rotors are made with cast iron. Besides having economical advantage, cast iron rotor provides many disadvantages due to its weight, such as reduction in fuel efficiency, increase in green house gas emission, and increase in noise, vibration and hardness. With the development of commercial aluminum composites, composite brake rotors are now manufactured. However, the present commercial composite materials are not specifically made for brake application and there are drawbacks. A major drawback is their poor elevated temperature property. In this paper, the unique properties offered by an aluminum composite for brake application is addressed, and an approach to compensate its properties for brake application is highlighted.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

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 communication0.0000.001
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 head0.016
GPT teacher head0.232
Teacher spread0.216 · 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