2020 Update on AFRL EXPEDITE Program Progress by Lockheed Martin
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.
Bibliographic record
Abstract
This paper provides a progress update on the Air Force Research Laboratory’s (AFRL) EXPanded MDO for Effectiveness-based DesIgn TEchnologies (EXPEDITE) program, led by AFRL’s Multidisciplinary Science and Technology Center (MSTC) and performed by a multi-company team led by Lockheed Martin Advanced Development Programs (ADP), also known as the Skunk Works®. The EXPEDITE team has made significant progress toward achieving the program objectives of advancing the industry’s early conceptual Multidisciplinary Analysis and Design Optimization (MADO) capabilities in several key areas. These areas include advancing Effectiveness Based Design (EBD), establishing and evaluating geographically distributed computing, and utilization of High-Performance Computing (HPC). The results of this effort will establish a conceptual design framework which enables insight in how early design decisions impact aircraft operational measures of effectiveness. This framework will also establish methods for near real-time business-to-business modeling and simulation collaboration between an airframe prime contractor and key tier 1 and tier 2 sub-contractors. This paper provides an overview of the advancements made to date in many key areas and discusses plans for future work.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it