Proceedings of the 2008 AOSD workshop on Aspect-oriented modeling
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
Aspect-orientation is a rapidly advancing technology. New and powerful aspect-oriented programming techniques are presented at many international venues every year. However, it is not clear what features of such techniques are aspect-oriented concepts and what features are rather language-specific specialties. Research in aspectoriented modeling has the potential to help find such common characteristics from a perspective that is at a more abstract level (i.e., programming language-independent). The Aspect-Oriented Modeling (AOM) Workshops bring together researchers and practitioners from two communities, aspect-oriented software development (AOSD) and software model engineering. The workshops provide a forum for presenting new ideas and discussing the state of research and practice in modeling various kinds of crosscutting concerns at different levels of abstraction. The goals of the workshops are to identify and discuss the impacts of aspect-oriented technologies on model engineering to provide aspect-oriented software developers with general modeling means to express aspects and their crosscutting relationships onto other software artifacts.
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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 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