Model management for regulatory compliance
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
Software has come to mediate many of the activities in life, including financial service platforms, social networks and vehicle control. As a result, governing bodies have responded to this trend by creating standards and regulations to address issues such as safety and privacy. In this context, the compliance of software development to standards and regulations has emerged as a key issue. For software development organizations, compliance is a complex and costly goal to achieve. They may have to comply with multiple standards due to multiple jurisdictions or to address different aspects of the software and these may overlap and conflict with each other. The evolution of standards must be tracked and changes assessed. Evidence for claims of compliance must be collected and managed. Finally, maintaining families of related software products (product lines) further multiplies the effort. In this paper, we propose to exploit the connection between the field of model management and the problem of compliance management and explore how to use model management techniques to address software compliance management issues.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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