ISSUE INFORMATION–TOC
Bibliographic record
Abstract
INCOSE's membership extends to over 10, 000 individual members and almost 100 corporations, government entities and academic institutions.Its mission is to share, promote, and advance the best of systems engineering from across the globe for the benefit humanity and the planet.INCOSE charters chapters worldwide, includes a corporate advisory board, and is led by elected officers and directors.For more information, click here: The International Council on Systems Engineering (www.incose.org)INSIGHT is the magazine of the International Council on Systems Engineering.It is published four times per year and features informative articles dedicated to advancing the state of practice in systems engineering and to close the gap with the state of the art.INSIGHT delivers practical information on current hot topics, implementations, and best practices, written in applications-driven style.There is an emphasis on practical applications, tutorials, guides, and case studies that result in successful outcomes.Explicitly identified opinion pieces, book reviews, and technology roadmapping complement articles to stimulate advancing the state of practice.INSIGHT is dedicated to advancing the INCOSE objectives of impactful products and accelerating the transformation of systems engineering to a model-based discipline.Topics to be covered include resilient systems, model-based systems engineering, commercial-driven transformational systems engineering, natural systems, agile security, systems of systems, and cyber-physical systems across disciplines and domains of interest to the constituent groups in the systems engineering community: industry, government, and academia.Advances in practice often come from lateral connections of information dissemination across disciplines and domains.INSIGHT will track advances in the state of the art with follow-up, practically written articles to more rapidly disseminate knowledge to stimulate practice throughout the community.
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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.916 | 0.893 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".