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Record W4388015285 · doi:10.4271/2023-01-1652

Supporting the Transportation Industry: Creating the GC-LB and High-Performance Multiuse (HPM) Grease Certification Programs

2023· article· en· W4388015285 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 International Journal of Advances and Current Practices in Mobility · 2023
Typearticle
Languageen
FieldEngineering
TopicSafety Systems Engineering in Autonomy
Canadian institutionsLanxess (Canada)
Fundersnot available
KeywordsGreaseCertificationAutomotive industryClass (philosophy)Computer scienceQuality (philosophy)Manufacturing engineeringEngineeringMaterials scienceManagementArtificial intelligenceComposite materialPhysics

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">This paper outlines the history and background of the NLGI (formerly known as the National Lubricating Grease Institute) lubricating grease specifications, GC-LB classification of Automotive Service Greases as well as details on the development of new requirements for their High-Performance Multiuse (HPM) grease certification program.</div><div class="htmlview paragraph">The performance of commercial lubricating grease formulations through NLGI's Certification Mark using the GC-LB Classification system and the recently introduced HPM grease certification program will be discussed. These certification programs have provided an internationally recognized specification for lubricating grease and automotive manufacturers, users and consumers since 1989. Although originally conceived as a specification for greases for the re-lubrication of automotive chassis and wheel bearings, GC-LB is today recognized as a mark of quality for a variety of different applications. The main driving force to upgrade GC-LB was that six of the 12 property test methods utilized in ASTM D4950 had major issues, requiring either revised, alternative or new test methods. In addition to the issues associated with the test methods, NLGI recognized that advancements in materials, technologies and applications would be better served by newer specifications. The initiative that began as an update to the GC-LB specification then led to the introduction of the HPM specifications.</div><div class="htmlview paragraph">Analysis of GC-LB certified greases showed that most commercial greases also claimed other enhanced properties such as high load carrying, saltwater rust resistance, water resistance and long life in addition to meeting the GC-LB requirements. By 2019, NLGI’s Specification Working Group had developed a draft specification with proposed changes to upgrade the GC-LB classification. This draft was further modified through interviews, surveys and in-depth discussion with members of the lubricating grease industry. The initial focus was on updated specifications for a High-Performance Multiuse grease that could be used in a variety of bearings and applications which require similar lubricating properties. Additional specifications were defined as part of the HPM specification for all these properties except long life. Long life (+LL) and High Temperature (+HT) properties are currently being addressed in Phase 2 of the HPM Grease Certification Program. Additionally, the low temperature specification was added to the HPM specification after interest was shown during the interview and feedback process.</div></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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score0.289

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.030
GPT teacher head0.336
Teacher spread0.306 · 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