Logistics support system; harmonization enhances multi-national support
Bibliographic record
Abstract
This Paper examines the evolution of the Harmonization approach for the LM-STAR®Multi-National Support. Critical to the Lockheed Martin Corporation's approach to winning the JSF/F35 contract in 2002 was developing a common logistics approach. A strategy was devised for ATE Harmonization whereas all Original Equipment Manufacturers (OEMs) would utilize a common ATE subset solution knowing one day programs developed on the subset solution would be required to execute on a full up solution for Depot support, etc. Lockheed Martin Simulation, Training & Support (LMSTS) was already executing the Consolidated Automated Support System (CASS) and some of its early PBL efforts, Contractor Logistic Support (CLS) efforts, and the Consolidated Service Pool Program (CSP) and realized how a common solution was beneficial to the US Navy and other Foreign Military users of CASS. A test envelope was established using the CASS as a baseline. Several OEM/supplier meetings were held and the test envelope was expanded to handle additional OEM test requirements. The first station built was a full-up superstation with the entire test envelope supported. From this point, each OEM working with their Lockheed Martin Aerospace buyer, filled out a requirements needs as well as a quantity and need date. From these requirements LMSTS developed various configurations and delivered 62 System Design & Development (SDD) testers to OEMs in the United States, United Kingdom, and other JSF partnering countries. LMSTS is now delivering 16 more LM-STARs®in Low Rate Initial Production (LRIP) 3 to the OEMs and in LRIP4 LMSTS will deliver 21 stations to OEMS and three to the Depot.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".