Bibliographic record
Abstract
Nowadays, knowledge is viewed as a significant asset for organizations. Consequently, knowledge management has become an important factor to take into account within and between organizations. This paper proposes an approach for acquiring knowledge used in information system (IS) development. It is argued that an IS development process may include several IS development and maintenance projects, which could be carried out in parallel, and each project may use its own software process and development method. In order to support the different activities of the IS development process, it is suggested that the development process itself needs an IS to manage its knowledge. We called this type of IS: Information System upon Information Systems (ISIS). An ISIS is considered as a new infrastructure which coexists with other IS infrastructures. It aims at managing the knowledge used in IS development. Knowledge management involves activities such as acquiring, analyzing, preserving, and using knowledge. In this paper, we suggest an approach for acquiring knowledge used in the IS development process, including its identification and organization.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".