Supporting the Transportation Industry: Creating the GC-LB and High-Performance Multiuse (HPM) Grease Certification Programs
Bibliographic record
Abstract
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. 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. 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.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".