Bibliographic record
Abstract
As of 1 August 2007, SourceForge.net hosted more than 150,000 registered open source software projects, and many more projects are available on other sites. With so many OSS choices, it might seem that building a new application is only a matter of finding the appropriate projects and putting them together. We've developed the adaptable multi-interface communicator infrastructure to support rapid prototyping from OSS components. AMICO is based on existing middleware platforms for component integration, but it focuses on pragmatic aspects of OSS integration often absent from existing integration platforms. AMICO satisfies requirements based on our experiences in solving practical problems in several projects. AMICO OSS is based on a publish-subscribe infrastructure for integrating loosely coupled services. In such infrastructures, a publisher updates a shared data repository. The loosely coupled approach can be highly adaptable when using simple data structures, because new applications can use existing data in the model and add their own without breaking the infrastructure. Components communicate by exchanging events through a shared data repository consisting of named slots called variables. Components can update the variables and register for notifications about variable changes. Modules can also derive new variables by processing existing ones.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.021 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.160 | 0.278 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".