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Record W2247979159 · doi:10.4271/2003-01-0794

Application of Nylon Composite Recycle Technology to Automotive Parts

2003· article· en· W2247979159 on OpenAlexaff
Denise Carlson, Hiroyuki Yamazaki, Sunao Fukuda, Christian Leboeuf, H. Peter Kasserra

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsDuPont (Canada)
Fundersnot available
KeywordsAutomotive industryComposite numberManufacturing engineeringComputer scienceAutomotive engineeringMaterials scienceEngineeringComposite materialAerospace engineering

Abstract

fetched live from OpenAlex

Recently there has been a market trend requiring End of Life Vehicles to be recycled to satisfy current legislation; therefore, we are approaching the recyclability of automotive parts based upon these environmental requirements. At this time, we have demonstrated a new recycle technology for polyamide using one of the largest automotive applications, the radiator end tank which has been previously viewed as degraded material due to hydrolysis and deemed as shredder residue. This technology [1] allows for the recovery of the base resin that is then recycled into a radiator end tank with performance equivalent to one made of virgin resin. The process for this technology includes collection of post consumer radiator end tanks that are then reground, dissolved, filtered for glass fiber removal, precipitated, recovered, and compounded into a usable resin. This technology is referred to as “Nylon Composite Recycle”.

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: 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
Bibliometrics0.0010.000
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 head0.008
GPT teacher head0.252
Teacher spread0.244 · 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

Citations5
Published2003
Admission routes1
Has abstractyes

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