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Record W2603285147 · doi:10.4271/2006-01-0522

The USAMP Magnesium Powertrain Cast Components Project

2006· article· en· W2603285147 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

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2006
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Properties and Applications
Canadian institutionsChrysler (Canada)
FundersU.S. Department of Energy
KeywordsPowertrainMagnesiumAutomotive engineeringComputer scienceMaterials scienceMetallurgyEngineeringPhysicsTorque

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">Over the past five years, the US Automotive Materials Partnership (USAMP) has brought together representatives from DaimlerChrysler, General Motors, Ford Motor Company and over 40 other participant companies from the Mg casting industry to create and test a low-cost, Mg-alloy engine that would achieve a 15 - 20 % Mg component weight savings with no compromise in performance or durability. The block, oil pan, and front cover were redesigned to take advantage of the properties of both high-pressure die cast (HPDC) and sand cast Mg creep- resistant alloys. This paper describes the alloy selection process and the casting and testing of these new Mg-variant components. This paper will also examine the lessons learned and implications of this pre-competitive technology for future applications.</div>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.954
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.019
GPT teacher head0.251
Teacher spread0.233 · 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