Women's Engineering Institute (WEI) at Embry-Riddle Aeronautical University
Bibliographic record
Abstract
in 2011 where she was awarded the Senate Medal for Outstanding Academic Achievement for her doctoral thesis on large-scale parallel simulation.For the past eight years she has been conducting research on discrete-event modeling and simulation, distributed and parallel simulation, software engineering, and integrated modeling environments.Dr. Jafer has been previously involved in projects dealing with modeling and simulation of natural disasters as well as emergency response to natural fire.She is currently conducting research in disaster engineering, modeling and simulation in aviation, and large-scale NAS (National Airspace System) data analysis.Dr. Jafer has served as committee member and organizer of the Annual Spring Simulation conference, and she is now the co-chair of the Annual Simulation Symposium (ANSS).She will be serving as the Proceedings Chair of the Spring Simulation 2015 conference.Dr. Jafer values and promotes women in Science and Technology and is an active member of the SWE and IEEE WIE.She is currently leading the Women's Engineering Institute initiative at Embry-Riddle.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.152 | 0.046 |
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".