Self-registering plug-ins: an architecture for extensible software
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
Extensibility and flexibility are essential characteristics of today's software. A common technique that offers these vital features is the concept of plug-ins, in which additional components are able to easily "plug" into the application on-demand to provide extra features or functionality. Plug-ins are indispensable in software as they offer tremendous advantages in terms of giving the application simplified means to keep pace with today's rapidly changing technology. This paper describes a powerful and flexible plug-in architecture, which builds upon an improved version of the pluggable factories design pattern. The framework for the plug-in architecture in this paper consists of a registry implemented via a map that would contain a reference to each plug-in, which is used to create instances of it upon request. The plug-in is automatically self-registered at start-up before any code is executed by using static instantiation. Thus, new plug-ins are dynamically recognized without any interference from the user.
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 | 0.001 | 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