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
One of the lasting challenges in building distributed fault tolerant systems is keeping application code size and complexity down. This can be done by capturing the nuances of distributed computing environment and redundant fault tolerant elements into a common infrastructure layer, thus factoring the code that would otherwise need to be written again and again by each distributed fault tolerant software component. When the application code has many complexities, and Air Traffic Control (ATC) is certainly one such example, achieving this goal becomes paramount.Under a project called En Route Automation Modernization (ERAM), the Federal Aviation Administration (FAA) is developing a replacement for its aging en route assets. At the same time, a foundation is being created for the anticipated future enhancements, driven by the projected increase in air traffic. At the core of the ERAM design is a distributed object oriented (OO) framework called Publisher FrameWork (PFW), which is ERAM's answer to the aforementioned OO challenge. This paper describes the PFW properties, the experiences with it accumulated through the first build of the ERAM program, and its applicability to fault tolerant computing.
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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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